{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Adding New Anomaly Detection Models\n",
    "\n",
    "This notebook provides a minimal example on how to add a new anomaly detection model to Merlion. We follow the instructions in [CONTRIBUTING.md](https://github.com/salesforce/Merlion/blob/main/CONTRIBUTING.md). We suggest you review this [notebook](1_AnomalyFeatures.ipynb) explaining how to use a Merlion anomaly detection model before reading this notebook.\n",
    "\n",
    "More specifically, let's implement an anomaly detection model whose anomaly score is just equal to the value of the time series metric (after mean and variance normalization). By default, we want the model to fire an alarm when the value of the time series metric is more than 3 standard deviations away from the mean value.\n",
    "\n",
    "Note that this is already implemented [here](https://github.com/salesforce/Merlion/blob/main/merlion/models/anomaly/stat_threshold.py) as the `StatThreshold` algorithm. For a more complete example, see our implementation of [Isolation Forest](https://github.com/salesforce/Merlion/blob/main/merlion/models/anomaly/isolation_forest.py)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Config Class\n",
    "\n",
    "The first step of creating a new model is defining an appropriate config class, which inherits from `DetectorConfig`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from merlion.models.anomaly.base import DetectorConfig\n",
    "from merlion.post_process.threshold import Threshold\n",
    "from merlion.transform.normalize import MeanVarNormalize\n",
    "\n",
    "class StatThresholdConfig(DetectorConfig):\n",
    "    # If the transform argument is not provided when initializing the config,\n",
    "    # we will pre-process the input by normalizing it to be zero mean (but\n",
    "    # not unit variance!)\n",
    "    _default_transform = MeanVarNormalize(normalize_scale=False)\n",
    "\n",
    "    # When you call model.get_anomaly_label(), you will transform the model's\n",
    "    # raw anomaly scores (returned by model.get_anomaly_score() into z-scores,\n",
    "    # and you will apply a thresholding rule to suppress all anomaly scores\n",
    "    # with magnitude smaller than the threshold. Here, we only wish to report\n",
    "    # 3-sigma events.\n",
    "    _default_threshold = Threshold(alm_threshold=3.0)\n",
    "\n",
    "    def __init__(self, **kwargs):\n",
    "        \"\"\"\n",
    "        Provide model-specific config parameters here, with kwargs to capture any\n",
    "        general-purpose arguments used by the base class. For DetectorConfig,\n",
    "        these are transform and post_rule.\n",
    "        \n",
    "        We include the initializer here for clarity. In this case, it may be\n",
    "        excluded, as it only calls the superclass initializer.\n",
    "        \"\"\"\n",
    "        super().__init__(**kwargs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Class\n",
    "\n",
    "Next, we define the model itself, which must inherit from the `DetectorBase` base class and define all abstract methods. See the API docs for more details."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "from merlion.evaluate.anomaly import TSADMetric\n",
    "from merlion.models.anomaly.base import DetectorBase\n",
    "from merlion.utils import TimeSeries\n",
    "\n",
    "\n",
    "class StatThreshold(DetectorBase):\n",
    "    # The config class for StatThreshold is StatThresholdConfig, defined above\n",
    "    config_class = StatThresholdConfig\n",
    "\n",
    "    # By default, we would like to train the model's post-rule (i.e. the threshold\n",
    "    # at which we fire an alert) to maximize F1 score\n",
    "    _default_post_rule_train_config = dict(metric=TSADMetric.F1)\n",
    "\n",
    "    @property\n",
    "    def require_even_sampling(self) -> bool:\n",
    "        \"\"\"\n",
    "        Many models assume the input time series is sampled evenly.\n",
    "        That isn't a necessary assumption for this model, so override the property.\n",
    "        \"\"\"\n",
    "        return False\n",
    "\n",
    "    @property\n",
    "    def require_univariate(self) -> bool:\n",
    "        \"\"\"\n",
    "        Specify that this model only works for univariate data.\n",
    "        \"\"\"\n",
    "        return True\n",
    "\n",
    "    def __init__(self, config: StatThresholdConfig):\n",
    "        \"\"\"\n",
    "        Sets the model config and any other local variables. We include the\n",
    "        initializer here for clarity. In this case, it may be excluded, as it\n",
    "        only calls the superclass initializer.\n",
    "        \n",
    "        :param config: model configuration\n",
    "        \"\"\"\n",
    "        super().__init__(config)\n",
    "\n",
    "    def _train(self, train_data: pd.DataFrame, train_config=None) -> pd.DataFrame:\n",
    "        # Since this model's anomaly scores are just the values of the time\n",
    "        # series metric, there is no model to train.\n",
    "        # In general, you should train your model here, and determine its\n",
    "        # anomaly scores on the training data.\n",
    "        return train_data\n",
    "\n",
    "    def _get_anomaly_score(self, time_series: pd.DataFrame,\n",
    "                          time_series_prev: pd.DataFrame = None) -> pd.DataFrame:\n",
    "        # The time series values (assuming a univariate time series) are the anomaly scores.\n",
    "        return time_series"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running the Model: A Simple Example\n",
    "\n",
    "Let's try running this model on some actual data! This next part assumes you've installed `ts_datasets`. We'll begin by getting a time series from the NAB dataset & visualizing it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Time series /Users/abhatnagar/Desktop/Merlion/data/nab/realKnownCause/ec2_request_latency_system_failure.csv (index 2) has timestamp duplicates. Kept first values.\n",
      "Time series /Users/abhatnagar/Desktop/Merlion/data/nab/realKnownCause/machine_temperature_system_failure.csv (index 3) has timestamp duplicates. Kept first values.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "from merlion.plot import plot_anoms\n",
    "from merlion.utils import TimeSeries\n",
    "from ts_datasets.anomaly import NAB\n",
    "\n",
    "# This is a time series with anomalies in both the train and test split.\n",
    "# time_series and metadata are both time-indexed pandas DataFrames.\n",
    "time_series, metadata = NAB(subset=\"realKnownCause\")[3]\n",
    "\n",
    "# Visualize the full time series\n",
    "fig = plt.figure(figsize=(10, 6))\n",
    "ax = fig.add_subplot(111)\n",
    "ax.plot(time_series)\n",
    "\n",
    "# Label the train/test split with a dashed line & plot anomalies\n",
    "ax.axvline(metadata[metadata.trainval].index[-1], ls=\"--\", lw=2, c=\"k\")\n",
    "plot_anoms(ax, TimeSeries.from_pd(metadata.anomaly))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we'll split the data into train & test splits, and run our anomaly detection model on it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get training split\n",
    "train = time_series[metadata.trainval]\n",
    "train_data = TimeSeries.from_pd(train)\n",
    "train_labels = TimeSeries.from_pd(metadata[metadata.trainval].anomaly)\n",
    "\n",
    "# Get testing split\n",
    "test = time_series[~metadata.trainval]\n",
    "test_data = TimeSeries.from_pd(test)\n",
    "test_labels = TimeSeries.from_pd(metadata[~metadata.trainval].anomaly)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "                     anom_score\n",
       "timestamp                      \n",
       "2013-12-02 21:15:00   -9.065700\n",
       "2013-12-02 21:20:00   -8.097140\n",
       "2013-12-02 21:25:00   -6.908860\n",
       "2013-12-02 21:30:00   -4.892315\n",
       "2013-12-02 21:35:00   -3.703186\n",
       "...                         ...\n",
       "2013-12-14 16:25:00   15.041999\n",
       "2013-12-14 16:30:00   14.494303\n",
       "2013-12-14 16:35:00   16.234568\n",
       "2013-12-14 16:40:00   15.160902\n",
       "2013-12-14 16:45:00   15.055357\n",
       "\n",
       "[3403 rows x 1 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Initialize a model & train it. The dataframe returned & printed\n",
    "# below is the model's anomaly scores on the training data.\n",
    "model = StatThreshold(StatThresholdConfig())\n",
    "model.train(train_data=train_data, anomaly_labels=train_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                     no post rule  with post rule\n",
      "2013-12-14 16:50:00     14.520900             0.0\n",
      "2013-12-14 16:55:00     15.065935             0.0\n",
      "2013-12-14 17:00:00     15.825172             0.0\n",
      "2013-12-14 17:05:00     13.846644             0.0\n",
      "2013-12-14 17:10:00     15.050966             0.0\n",
      "...                           ...             ...\n",
      "2014-02-19 15:05:00     15.152393             0.0\n",
      "2014-02-19 15:10:00     14.771146             0.0\n",
      "2014-02-19 15:15:00     14.102446             0.0\n",
      "2014-02-19 15:20:00     15.023830             0.0\n",
      "2014-02-19 15:25:00     13.870839             0.0\n",
      "\n",
      "[19280 rows x 2 columns]\n"
     ]
    }
   ],
   "source": [
    "# Let's run the our model on the test data, both with and without\n",
    "# applying the post-rule. Notice that applying the post-rule filters out\n",
    "# a lot of entries!\n",
    "import pandas as pd\n",
    "anom_scores = model.get_anomaly_score(test_data).to_pd()\n",
    "anom_labels = model.get_anomaly_label(test_data).to_pd()\n",
    "print(pd.DataFrame({\"no post rule\": anom_scores.iloc[:, 0],\n",
    "                    \"with post rule\": anom_labels.iloc[:, 0]}))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                     anom_score\n",
      "time                           \n",
      "2013-12-16 06:40:00   -3.024196\n",
      "2013-12-16 06:45:00   -3.012073\n",
      "2013-12-16 07:00:00   -3.468464\n",
      "2013-12-16 07:05:00   -3.124039\n",
      "2013-12-16 07:10:00   -3.491421\n",
      "...                         ...\n",
      "2014-02-09 11:35:00   -4.819248\n",
      "2014-02-09 11:40:00   -4.823173\n",
      "2014-02-09 11:45:00   -4.822201\n",
      "2014-02-09 11:50:00   -4.677379\n",
      "2014-02-09 11:55:00   -4.300280\n",
      "\n",
      "[721 rows x 1 columns]\n"
     ]
    }
   ],
   "source": [
    "# Additionally, notice that the nonzero post-processed anomaly scores,\n",
    "# are interpretable as z-scores. This is due to the automatic calibration.\n",
    "print(anom_labels[anom_labels.iloc[:, 0] != 0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualization\n",
    "\n",
    "Qualitatively, we can plot the anomaly score sequences to see the difference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "no post rule\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"no post rule\")\n",
    "fig, ax = model.plot_anomaly(test_data, filter_scores=False)\n",
    "plot_anoms(ax, test_labels)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "with post rule\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"with post rule\")\n",
    "fig, ax = model.plot_anomaly(test_data, filter_scores=True)\n",
    "plot_anoms(ax, test_labels)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Customizing the Post-Rule\n",
    "\n",
    "The example above uses a simple threshold as the post-processing rule. As a result, the model is continuously firing alerts when the differenced time series value is far from 0. We support an alternative option which combines successive alerts into a single alert. We demonstrate this below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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374cMGcLnrhZSXl6OxYsX46GHHuK9zSkpKWjWrBluv/12RQLcHzt9MXPmTJSVlSEpKQm9e/dGRkaGot/FxcXhp59+wqJFi9CwYUOkpKTgX//6FyoqKgBUxXA3bdoU8fHxeP/99/Hll18GZJ8vRowYgaNHjyIlJQWdO3fmlz/11FPYuXMnateujWHDhmHkyJGybdx+++3o3LkzmjZtisGDB2PcuHH8dxEREVi5ciV2796NZs2aISkpCdOmTcOlS5c02R+CIEIHC+fr3RxBEARBEAQRMAcPHkS7du2MNoMIAPG5I48zQRAEQRBENWD58uWwWCw4dOiQoXbUqlVL8boulwszZsxAx44dkZ6ejp49e+LEiRMaWucdEs4EQRAEQRDVgIULF+Kaa67hUzqGAl9//TXOnj2LvXv34q+//sKyZcv4olyBEkwlWhLOBEEQBEEQYU5xcTE2btyIjz/+2G1+xG+//Yb+/ftj9OjRaNu2LSZOnMhno1m3bh26du2K9PR03HXXXfx8hqZNm+L//u//0KVLF/To0QM7d+7EjTfeiBYtWuD999/ntzdw4EB069YN6enpWLFihYdNd9xxB5YvX85/njhxosd6586dQ4MGDfjJxmlpaUhMTAQArFmzBt26dUPnzp0xcOBAAEBeXh5uueUWdOrUCb1798bevXsBAE8//TRuv/129O3bF7fffjtycnIwatQo9OzZEz179sSmTZsUHUeborUIgiAIgiCI4Jk5E5Ap8BMwXboAgswwUqxYsQIZGRlo3bo16tatix07dqB79+4AqkrX79+/Hw0bNkTfvn2xadMm9OjRA1OmTMG6devQunVr3HHHHXjvvff4XP+NGzfG7t278cgjj2DKlCnYtGkTysvL0bFjR9x7772Ijo7GsmXLEB8fj9zcXPTu3RsjRoxwSzM6depUvP7667jllltw6dIl/PHHHx6TpceOHYtrrrkGv//+OwYOHIhJkyaha9euyMnJwd13340NGzagWbNmyMvLA1A1Sbhr165Yvnw5fvnlF9xxxx18QaUDBw5g48aNiImJwW233YZHHnkE11xzDU6fPo0bb7wRBw8e9HmoQ1o4W61WREdHG22GOz4KCCgmIkKddlSA4zhNcvQSxkPnNjyh86oANfpqnfvpkD+vYTg+KmXZsmUoKysDAKRlZyNGXOCH44Agzm1ZdjYyd+70us7777+PCRMmYOfOnejbty/eeOMNPPLIIzhy5AjatWuH7OxsZGdnIzU1Fb/99hsyMzORnJyM4uJi7Ny5E3369MHixYtx3XXXobKyEs2aNcPOnTsRHx+PFi1a4OjRowCq8u+vX78e0dHReO2117Bz505YrVZkZmbi559/Rp06dXib+vXrh/vvvx85OTn49ttvMWrUKNhs7tI0LS0Nhw8fxi+//IJffvkFAwcOxDfffIPS0lJcd911aNasGQDw7W7cuBHffvstgKrsUBcvXkRhYSGAqow8MTExAIC1a9fiwIED/HYKCwtRXFzsM/46pIVzdHQ0jh07ZrQZbthXrYKldu2g2uAuXULksGEqWRQ8OTk5SE5ONtoMQgPo3IYndF59E2xfbUQ/HernNRzHR6VcvHgRrVu3rvrw2Wce3zscDg/B6A81ACR4+T4vLw87duzA6dOnYbFY4HQ6YbFY8NFHH+HixYuoU6cOOnbsCKAqJ39KSgpatmyJ2NhYfnl2djbi4+PRsWNHREVFoVOnTkhKSsLOnTuRnZ3NrxcdHY1WrVph9erVcLlc2L17NyIjI9G6dWs0bdrUoyroHXfcgQULFmDRokX49NNPpfevRg0MGTIEQ4YMQf369bF8+XIMHjzY7+MUGxvL/+1yufDnn3/67YClGGeCIAiCIIgwZunSpbjttttw9OhRHDlyBMeOHUPTpk2xceNG2d+0bt0ap06dwt9//w0A+Oqrr/jy9kq4dOkSkpOTERkZid9++82t8qmQKVOm8AWI2rdv7/H9zp07cfbsWQBVYnfv3r1o0qQJevfujQ0bNvAZNlioxrXXXsvnkP/tt9+QlJSE+Ph4j3YHDx6Mt99+m/+8W2H4DAlngiAIgiCIMGbx4sW4+eab3Zbdcsst+Prrr2V/Ex0djXnz5uG2225Dt27dYLVaMX36dMXbZGEh3bp1w5dffok2bdpIrle/fn20a9fOo6AUIzs7GzfddBM6duyITp06wWaz4cEHH0RycjLmzZuHkSNHonPnznwRo6effho7duxAp06dMGvWLNkCU2+99Ra2b9+OTp06oX379vykRl+EdAGUmjVrUqiGDoT660FCHjq34QmdV99QqIb+hOP4qBS3UA0Jgg3VCCX27duHbt268Z9LS0uRnp7OV/00G1QAhSAIgiAIgjCctWvXol27dnjooYdMKZqlqB6PNwRBEARBEISpuOGGG2Rjn80KeZwJgiAIgiA0JoQjY6stUueMhDNBEARBEISGREREID8/n8RzCMFxHC5evOiRro5CNQiCIAiCIDQkLi4O+fn5yM3Nlfze6XQiIgQLuwRCTk6Oogp9ZiA6OhppaWluy0g4EwRBEARBaEhERAQSEhJkv8/JyUHdunX1M8hAevXqhZKSEqPNCBgK1SAIgiAIgiAIBZBwJgiCIAiCIAgFkHAmCIIgCIIgCAWQcCYIgiAIgiAIBZBwJgiCIAiCIAgFkHAmQhaO4/DVV18ZbQZBEARBENUEEs5EyOJwOPD5559TQnmCIAiCIHSBhDMRsjDBTMKZIAiCIAg9IOFMhCwOhwNAVcUlgiAIgiAIrSHhTIQsLpcLALBhwwaDLSEIgiAIojpAwpkIWZhwPnPmjMGWEARBEARRHSDhTIQsLESDhWwQBEEQBEFoCQlnImRhHueVK1cabAlBEARBENUBEs5EyMI8zuXl5QZbQhAEQRBEdYCEMxGyUDYNwoz89ttvKCsrM9oMgiAIQgNIOBMhy7lz54w2gSA8mDNnDjZt2mS0GQRBEIQGkHAmQpYff/zRaBMIQhK73W60CQRBEIQGkHAmQhbKpkGYlQsXLhhtAkEQBKEBJJxDBJfLhY0bN2Lz5s2y65w/fx5vvfWWjlYZC3sdHhkZabAlBOFOo0aNjDaBIAgTc+zYMaNNIALEZrQBhDKGDh3K/71s2TLExMS4ff/SSy/h119/BQDMmDFDV9uMhl6LE2ajoqLCaBMIgjAppaWleOCBB7B69WpYreS/DDXojKlMSUkJKjUeNGfOnOn2meM4XjQDwMmTJzXdPkEQ0pw/fx4AqtWbH4Ig/IM5e/bt22ewJUQgkHBWmc2bN2Pzn38G3Q6L33U4HB7ZI06dOoXly5fzn4cMGeL2/Y4dO4Lefqixf/9+o00gCOzZs8doEwiCMDmUSjW0oVANDfB1U3Ach+wLF1A/JUXy+9ycHNw5fLjXNt5//30kJSXh+eef9/huwYIFGDVqlHKDQ5TY2FiUlJQAqPL0dejQwWCLgqOgoAARERGIi4sz2pSwx+l0IiIiQvV2P/30U9XbJAhCP0pLSxEdHa1pCAXTCJmZmejUqZNm2yG0gTzOAVBYWOj1e4vF4vX7C+fPY+26dbLfuzhOkR1SohkAysrKqkW4BhPNAPDKK68YaIk6jB8/Hg888IDRZlQLhg0bhlOnTqnervCaJIjqhMvlQlZWltFmBM3IkSOxbNkyTbfBQjUopCs0IeHsJ3l5eRg7dqzXdXwJ58rKSq/fq+EJu/fee4Nuw2xUVlZi9+7dRpuhKdnZ2UabUG24dOmS6m3abPQSj6ierF+/HlOnTjXaDFX48MMPNW2fJrR75/XXX0eHDh3QsWNHTJgwAeXl5Uab5AYJZz9RMlvel3DmLnuUOTnPskKPc3Vj7dq1mDVrltFmaI7ZOolwRfb+CwIqtU1UV1h6NS3uq3CDahDIk5WVhbfeegvbt2/Hvn374HQ6sWjRIqPNcoOEswG4XC4A2ncwBw8e1LR9vakugvKpp54y2oSw4/z588jIyEBeXp6q7X7zzTdU7IQgACxZsgQACWclMA3gjdLS0mp7LB0OB8rKyuBwOFBaWoqGDRsabZIbJJz9xJc3Wck6+w8cACDfwcjdKqtXr0b9+vVl212wYIHb50ceecSrHaHGvHnzAABHjhwx2BJtocwM6jNlyhQAwG233cYvU2NQ+vjjjzF58uSg2yEIf9mzZw9ycnIUrZuRkYFvvvlGU3v69u0LADhz5oyuadbOnz8f1L383Xff4U8/M2E5HA6cPn3aY3lhYSH+85//+Py9EntHjhyJ3377zS+7QgWHw4EePXrw/9jYDgCpqal47LHH0LhxYzRo0AC1a9fG4MGDDbTWExLOfsIueG9PjL5m47LYSrmbRy4G2mq1Yv78+ZLfdezYEUlJSV63Gy6sWLGC//v666830BL1oFf8BEH4w7/+9S+88847itf/+OOPNbQG6NmzJwDg/vvvx2OPPabptoRMmTIFDz30UMC/f/fdd/H0009j//79bmPy0aNHZX+zcuVKTJ8+3WP52LFjsW3bNmRkZHjdpjDzltSEYmbH33//7dP+UMRms2H79u38P+GxzM/Px4oVK3DixAmcPXsWJSUlHk5Bo9FMON91112oV68eOnbsyC/Ly8vDoEGD0KpVKwwaNAj5+fkAqi6SGTNmoGXLlujUqRN27typlVlBs2rVKgDeY5TOnDmjrDEZ4Xz48GGPZStXruT/XrNmjdt33bt3x6uvvgqgeszSXbduHR+2kZ6ebrA16lBUVGS0CdUGNmhV19egRPjgr6dUSyIjIwEYk6NYDYH56KOPuo3r3kID33//fZ/tefMWCx1vUm+od+3aBSD8365KsXbtWjRr1gzJycmIjIzEyJEj8ccffxhtlhuaCecpU6Z4CLw5c+Zg4MCBOHr0KAYOHIg5c+YAAH744QccPXoUR48exbx583DfffdpZVbQsDRv7AYrLS318BDHx8fL/l44WMsN3Kzj+eyzzzBv3jwsXbrUY7b+/Pnz8cEHH+Ddd991S0vXunVrr/YXFRWFhWBgnZqwcwvlGOjMzEyjTag2fPTRR0abQBCGk5+fryjWVilqtmUUwjHE3zzO4nF1zpw5yMnJwaZNm1BQUOD2nfDh4tixYygvL3dznrACZ6E8pgVK48aN8eeff/Ix3uvWrUO7du2MNssNzYTzddddhzp16rgtW7FiBR8POHnyZP7iWLFiBe644w5YLBb07t0bBQUFHtXyzAJ7reJ0OlFaWoqRI0dixIgRbuuwJ28pmJcdAJwyHU29evUAACkpKWjcuDFq1qzpsU79+vXRpEkTNG/e3OOJ9d///rfs9seMGeNRaTAUYZ3M1VdfzS8L5WpM4sIZW7ZsMciS8EctL044PIAS4Y9QfAmzQk2YMAH/+Mc/VNuOESnWgk0pKc6S9cILL/B/P/fcc5K/kes/pN5C33777Xjuuecwfvx4Nweb8CHj8ccfxy233IInnniCD/E4cHkelLdwkXClV69eGD16NLp164b09HS4XC7JsBgj0TXp6IULF9CgQQMAVaKQzUbPyspCo0aN+PXS0tKQlZXFrytk3rx5fCC5w+FQPDlCLc6dO4eEhAQcOXIEr7zyChISEgBUZbCIiYlBZXQ0ImJikCsTs1rocMAVEwMAOHr2rOQ+RiQm4qabbgp439q0acPbdf78eT4vtMPh4Jf707ZQ7BsJsz0xMRGLFy9GQkICKioq+OXZ2dmoVauWcQYGQU5ODr8fQFUey7ffflvz7Zrh3L711ls4evSopvsrPLZZWVlISEhAcXFxUP0Hx3Ee9xP7HB8fr3vfJMQM59XsOCorYQlibgFXWQmbzudYeF6V9uVlZWX8un///Tfq1auH4uJiJCQk4Pz586pdp0VFRW73mVS7wR5zwP24Hzx4kN/m6dOnEXN5bFVKfn6+m80nT570uQ8vvPCC5LEvLy93+62YJUuWYNCgQQA8jxUAvmLsmTNnEBsbC5vNhjZt2hjajxjFM888g2eeecZoM2QxLFu/xWJRlKFCzPTp0/mnj5o1ayI5OVlt07zCXrk8+eSTbstZBouH27VDarNmSJK5gW3l5bBe7jjSEhORKLFeicsFm80W1L4xO+Pi4hAbGwsAOH78OL/c37b1Ps5SMNsLCgrQpEkTFBQUoHHjxnj++efx4IMPIjIy0hR2BoL4VR6g3zE3+pht27ZNUzuKi4slj29sbGxQ27Tb7R73E/vcoUMHw4+r0ds3O/aoKFj8FFpCuMpKRBpwjMXXmq/zXFBQwK/76KOPYs2aNXA6nfyy/Px8tGzZMugS0w6Hw+0+k7Ir2GMOuB/3n376id/m+++/jxdffNGvtvbs2SPZNzCk9kGYflL4/RdffOG1rc8//5zP6nPy5EkkJSV5xGYXFBTg7rvvRmRkJOx2O7Zs2WJqAVld0TWrRv369fkQjHPnzvEhCampqW4T6jIzM5GamqqnaYpQMiEAgNcCJsKHBU4mVMPlcnkN9/AH4Wu6+++/X5U2zQCbeGGxWPgcj+HWwVAogDqwycYTJ050Wx5sTKa331OBA0IvfPUTUtfiAw88wP89Y8YMvPHGG0HbYUQ8rjDtXSBJBdikejk++OADRUXPAOD7779XvF2Xy+XVO02VBc2NrsJ5xIgRfDq1+fPn4+abb+aXf/755+A4Dn/++Sdq164tGcJgJA6Hg4/J9oVSwbNt+3bJ5S6OU004i8WC3rhcLtXidYXxzEKYp8SscfH+IBT/n3zyiYGWhA9nz54FAAwcONBtebAx8Rs3bpRc3qdPH9mUkgShNqWlpV6/lxLO4hRoP/30E2bMmBGUHUZc81pvc9myZfjiiy8UrVtYWAgAitLCchznMeGfCB00E84TJkzA1VdfjcOHDyMtLQ0ff/wxZs2ahZ9//hmtWrVyK588dOhQNG/eHC1btsTdd9+Nd999VyuzAiY3N1fxut5ks0sQFynXputyqEYwyE1sYPizP8Gwb98+1SrhRUVFSS5nwjkcvHwsFyoAbNiwwUBLwge5EvfBepxZhh0hTZo0QYcOHchjROgGE2xyiB0+rDS2mGAnzQqveakJ7VogDi9hD8n+0rt3b9nvhGnllHi1n376aZ/rOByOgEJVCXOgmXBeuHAhzp07B7vdjszMTEydOhV169bFunXrcPToUaxdu5bPumGxWPDOO+/g2LFj+Ouvv9CjRw+tzAoYvwZZLx5njuN83jCcCqEaQgEmxaRJk0wfClBaWuoWT7Z+/XrJ9eQEdSgiHAjEWWnCkWBnxSuBXefiwfy1114Lql1hJTaO41BZWYlTp04hJiaGhDOhG76KoIiF89dff62JHcJr3pcXXC3++usvt8+KayiI8JYCV+idv3jxott3+fn54DjOLZVc48aNfRaAuXTpkqIJvLVr1/a5TjC4XC6sXbtW022EI1Q5UCH+CGevclSBcFbD4yxGqiOT8pipTTDifN68edWynPF///tfAIEPAqHE3Xffzf+tVR5Yljw/MTHRbXlRURE++OADVbbhcDj4Nx41atSgUA1CN7bLhPzJodWbLDO88Qv07Wb9+vXRokUL/vOjjz7K/y2s6ip2aFVUVODVV1/FmDFj+GVRUVG44YYb3Iq/CdcHgLfffhuHDh3yWbCsc+fO/u2IAsaPH88Xcjt9+rTPOG/CExLOCpETgCyFjGhl2XZcCoRzTm4uiouL/bLPF++9957HMvHTur/s3r0bzzzzDJYuXSoreoIRzsFWCyotLQ3Jinz169cHANWvATMifM3sbUa6L+QKyDz//PNuM9fFs+SXLVsW8DbF22fCISIigjzOhKaY7W0hx3E4dOiQ27JQK4gyZcoUAFVvpljaODFi4exwOLBu3TrJdV999VWsWbPGrRAcqwjIaN26Nb/OSy+95Pbd+PHjNXkYKSgo4FN/fvXVV6q3Xx0g4awQltJNzDfffIM777zTbZm3Tk1JqEZ5ebnqtdl//vlnj2VyoQ9KyM/Px6xZs7B582bMmzcPQ4cO9dpRBuKB8xW754snnnjC49yEAkw4VzcCnax35swZTJs2zeOtym+//eYxgU+rbD333XcfL5ZtNhsJZ0JTHA5H0OnjAKiSTQOoylEsnpyt51uXvn37BvxbVm33119/BeC9j2DhXv369QPg/8PB6dOnvbY9ePBg/nPbtm01L+rF4trN9iBmdkg4KyQ6OhqAewwqiy0bN24cnyHEYrF4F84uFywWC2w2m9fYXDU6RYZcvNn+/fsDblPqhpbqRNiyYG5MYbtpaWmKf5eTkxMSXlvxcQvVIi7BEqjYZBN2xDlRpV5JC1+pqg0LfUpNTaVQDUJTnE4nX9hKKaNHj3b7vGbNGrRt25avQRAMzJN63XXXudmoF8OHD+f/3rt3r6LfsBhjNraz8EglYZIshlnp/Br2Zpr19S1btpRcT1jJMTIyUvN+5Pz58wAo/Z2/kHBWSExMDMaNG8fHBgFwi4kaOnQogKpZ9b4kosViQaf0dLffC4mIiMDDDz8ctM0MoaAQPtEGg9QrJCnhzDpPtZ5oBwwY4PV7YUfj78BiFGyS2rXXXmuwJcYRERER8IQiFoYkLlsuFerTqlWrgLahBDaJqG7duqaI9yTCF6fT6fc8mEmTJkkuv/HGG4O2h/W7wv432FBAf2jevDn/99y5cxX9hr3RbNasGYAr/e/BgwcBVFX/FON0OtGtWzdERkaifv36ise1adOmAbgyDvbq1Uv2fNx3333o0qULXwRFDyjDh3+QcFaIxWLBnXfeCYvFgmXLlmHp0qVu3zdp0gRr1qyBzWbzejOxGGdvnunatWsrygWplH/+85/83zNnzlSlTWHcFkNKLLBZwcGkv3O5XPjll18AQPZhgyEUX2rlwlaTMolysyxGLtg8qqFGdnY2/7fT6Qw6POnw4cM+19FygGjQoAFatmyJyMhIxUUTCCIQKisr/comFBERwXtWpQj2oZ1d71OnTuXHhuPHjwfVpj8Is09cuHBBkaBl48OwYcMAgC/IxpAKFXS5XPzb4IiICA+vutwxrlGjBv97wPsbg5tvvhlz5szhJxnn5eUFNf9DCWYcK80MCecAiImJkc1TaQEUpaOzWCyylQM5jlMlVIN1CELUCgERJ9AHpL3KrJoUE76BYLfb+U5Y7hUXywkuFEZqhruoxa233oqMjAy3Zey4BRuiUVpaqnusWlZWVsDeVeaRatu2LQDgzz//DMoWb/GGbGAI5i3EzJkzPR6YhTidTlitVkRFRZHHmVCd0tJS5OTkAPDf4ywWeGIHBPO6BgoTzjGCctpCL7DeDBkyxOv3586dw1133QWgKn0cUOX8kmPZsmVYsGABXC4X34ecPXsWmzZtcltPztvNinfl5OSA4zg4HA6ffVFkZCSOHDmC2267DePHj1fkfDpx4gSeeOIJn9k6AHNkQQlVzKcswhxOgccZUCfMoH///kG3IUdeXp7HMqmYtsWLFwOoyusdKOXl5Xzbcp54tq/CvMBmFM4MKZEnFP0spMAfITxy5Ej89NNP/O/0SGc3depUt/K9/sBmdLOHq0C8HmKxLZcXWpyKLhAOHTqErVu3yn7PvEjs3tUzxpMIf1566SU8++yzAKBIeEnBJrWJcz8Hm/6UeVqFNv34449Btekv7du3d/u8e/duvv/MyMhw60vZA4g3hJO0P/jgAyxYsMBjUubmzZvdfiP3FoB5nNesWYPdu3crevARt7VixQqfNt93333YuXMnVq9e7XNdYVw44R/mVRYhis/JgQqEc35+viqTAqTySKqF+EkbkBYKLBtJsJMDpdKGScU7Cz3bp06dCnibWjNv3jyv3zPPjb9egddffx1AVZze3XffrYsHOtDjnJWVBQDo0aMH0tPTMW7cOL/bEFfpkstR++abbwII/mFq9+7dbp+vvvpqvlDNN998w8dHUrgGoTZbtmzh/z579qxbqJMc4j75//7v/yTD7IIVzsyjKnwTKxaVWvN///d/bp9nzZqFw4cP85WIpfpCyXSyl2HrCwX0V1995daHiO9xb5PX2RvF0tJS/u2UN8SOBGHBJcJYSDhrgDepwsIwLBaL1/XEA3QgiOM5lby+UQrzMPz3v/9Fw4YNAUh7UZmHw1/viDC+TG6ChPC1IMPMWTSEtomreYlhxy3Q12nMi2vm7A5ssL7qqqvw119/qZKCUaqK2tdff817nNV6C8Gu9aFDh/J2C73fUVFRGDdunGwecSPTP73++utBh8UQxvL9998DAB555BGv4o8JO19zW1ioRqBvSebPnw/gimdVL+Li4vjJ1eIc7UCVmP7uu+88lrP7r2nTprJts3WE1WuPHz/uVTh7m0PBHFkcxynKiqJFRVxKO6cOJJzVRkE6OqCqg/KWp9jbRI5A8TWxzh9Y59GnTx988sknSEpKkhTOTPj5e8MKxbKceBw5cqTX3+lJUVERHA6H11eA3nJ4imHxditXrgzIHuEkFLPC4tXT09Pdlh84cCCoDj4jI8Mtjlw4cUg8sIknBCmFnRc5zxGbEc+8ex988IFboYQhQ4bgxIkTAW07WH788Uf88MMPhmybUAd2X//9998oKirCjBkzJO8ZFlrEnBtydO3aFYD/VQiNpk6dOrLzjQD3ydjC48P+lrp3R4wY4bG+EOFvHA6HbHYMMcIQLmGstBxSwnnfvn2KtiUHCWd1IOGsMkpDNXbu2uX2qm3btm1un7WIz1UzPduYMWPcBI/VapUUaWyZv4nihQJHzmsqJXqMqlY1ZswYzJ49G7fffjuAKvEm9vIwL7AS2Ot/qZAYJbBr0Ol0YtmyZZgyZQpee+01PP/88wG1520bgcLOsVjM/uMf/8CxY8d8/l5JiIhYlIvvq0CzbLDXv3IPdew1K3u9vmzZMrzyyitu67BQFSOgAdS8jBw50udDFetX2VyTI0eOSM4jYdd7SkqKom17i+EPBK0f3B0Oh+IwE6kwLnHu98WLF+Pee+8FIH+PCMfRRo0aKb6XmJ2zZ8/Gjh07fPY9UnM+WP5oRmFhIT766CN8/vnnivJxS/VXvXv39vk7wh0SziqjJKuG1Wr1EHhHjhxxu4m1npHcoEGDoH5vs9nQpk0b/rPUPgHqzNyVa0P8RJ6UlITo6GiPrBXBpMLzB3HZ50OHDuHVV1/lP/vzFoF5iMRlbCsrK5GRkeGzlDh7hehwOPDBBx/g/Pnz+Omnnzwq6QVDsMJPrhonoEzY7dixg/9b7oFA/OpYPFgF+zAp96DGBj1vHiItH/LkJkkaxYkTJ0wdNmQmSktL8eCDD3pdh137QnH1+eefewhVNpla6ZuVVatWBTypWCq+V2oSuZrY7XY34ewtM8bevXuRkZGB4uJivn8RZ4eKj4/nHzbk+iDWh9x0002oVauWZIpRKYR9TXZ2Nj+RWw5fk6XPnz+PRYsWYcmSJdi0aRM/v8IbUg8ySh+qiCuQcFYbH7HL7Dup7BAlJSU4e/YsAKBDhw6qmDN9+nTJ5ZGRkbxXMxDET/oRERGSQkBpMnoxwrbE4RfiSSCM3NxcPvYPqEoyD3h6FbSCdagPPfQQv2zt2rX832IRJ8yvrRRW7crXPrEQAS09PsHG4ffr1w/t2rVzW8YekpR4goUTLOUmwjZq1Mjts7jdYPM6X3XVVZLL2UMdewUuRTDC+euvv+arfjHOnz+PjIwM7N69G//+978DblsL7rvvPkVZAYgqlN63o0aNcvvMUqwxpCZV++Luu++W/e6HH37Ahx9+6LaMXcdSoQVaF9YQj0NscrQULDypvLwce/bs8dm23P3J7ruIiAisX79e8XUt9oz7EroWi8VrPYdnn32WT4+pdIK21HWld1x6OEDCWWV8eZxxOVSjU3q6x5NednY2zvgRBxsMUsnb/UHcYcmFavjD+fPneW+HsNMSe5z79esnOTNcDPMY6JWInw0SR48edVvOYtldLpdbnLnS0rBCmDfk3LlzsutkZmbyNmiZqzNYD6LL5eK9VOzYBVqiXc6bP2HCBLfPanuc5bbLvEVS1cfU4NNPP/XwWP3+++8AvF8bRiKcSGW32xWlzCKu0Lp1a49lYq+kcCIboP7k4CVLluDbb791W8beqkmJZDUnpAtxuVwoLCz0GIdq1qyJpUuXen27Z7fbsWjRIp/bkOuD9u/fDwB+p50MpC9esGCB7Fin9MH7zz//REZGBjZt2oRPPvnE43vhHBBCGSScNUCJx9lqtUremH9fju1U60mdTXQQZqCYOnUqbr/99qA8XuI8okqEs6+n4kcffZT3dghtE5dS9sdGoOoVppaw8yh3zqZMmcLbE2zaJ3aMveVInTZtGv+q3p+46kBtCRRhFa4ePXoAuFL9T/zw4Q0W9yd1/H0JV+FvioqKFIWfMK+/N9h5Fpb4ZqEpc+bMASA/ML/66quKcuCK47XZA9quXbt8/nbr1q147733NJ8TkJGRwXsBmeAAqkJYmKj67rvv+LhSNSkvL/cZ0mQWMjMzMXv2bK/rsGuVlW8G4PHWQUvsdrvk/cFSgEqFXm3dulX1a4zjOAwdOhRjx45FYWGhx8ODxWLx2u/deeedirYzePBgycxNwu34QzBFwKQ4efKk1+8vXryIvXv38ik7n3vuOcmHVS3rPYQrJJzVxsfkwKpVLLDIxAQzgq0ix2AD+MMPP8wvYxP7fA0q33zzDR599FHJ744cOeLWOcmFagiRqjYo5OLFi/zfQlEmjvNVSkJCQkC/A6oGMqUdPhN5chk9WBnw5cuXy5aF/u9//6toW+xhQKkgZqE/WsD2N9ByrRs2bODDPZjoW7VqFQD/BAFLpSUO+1CC8F59+eWXMXXqVJ+/Wb9+vc91WFz9Rx99xC8rKSnBa6+9xk8YlOonSktLsXbtWq+vnBnigZvleZXLZQ0A999/P//3ihUrMHToUJ/bCRaphwDhJLQdO3b4FAGBcMstt2DMmDGqt6sFO3bswPr1670+5LPzLZxLkZqa6rXdgQMHBmVXRkYG33899dRTbt/t2LEDL774Iv9ZGLZ066238n+rnU//vOiNivitkVrlo6dOnYonn3xS9nuxE+T666/3q321xng5nn32WUXhgGYuFGZW6IipjMVi8R6qcZkIH8JZTd58800+LzBD7B1YunSpR6f9+eefu3mJhOzatQtff/01//n48eP8q2I5/PEiCo9NoAI4mMwB06ZN8zl5Q4yvSTVMcH3wwQf8MjZ5Rphk3xvsgUKpIBbGfKsNO/+Bep537drFv1pm8ZG//fYbAP/OHYtj/s9//uO3DULblT6MeHvgZFk85Nr66aef+MlEUvvoj4D05fEST5IF9AtbkkIocIShOVrHwYYC7BiwapqA+6v9kpISSQeCOIYfcH8jEhcXhy5dugRlGwuxEV8769atc3tIE6ZXZdmFAPUnZ58UCXFxbLWa2aOED+PvvfcegCtFU4TbmT59ut9zVu644w7F6wZSzEzOSSOGQjX8h4SzyligbND35XFWkzZt2ngMTqwIC7Nh3rx5bp024H9O5J07d3r93luBC5bei+FyudC4cWPceuutfKfhy7si5OzZs16P786dO30ef3GWDDmUdNTCa0I48/vXX38F4P2pX/hbNpgqPTdSr+1LS0tVme3OBlSXyxXQQ0rdunX5zCzikApfeWeZFwy4MnAmJiZizZo1+Oabb/D4449LFj5gsGtJ+OrZl4BjE3W+/PJLAHCbXLty5UosWLCA98AJH0z/+usvyfaEsYvl5eWorKyUfVCVQongzM3N9Yh7NYq2bdvyfwvTrVExFulzKRSq4kmAQtj1yFArfIP1j1J908WLFz3ip8eOHcv/LcytHGionRziN5dqpZiUwmazITIyEpGRkXyfwTKUCLcbiFgfNmyY4nWF3vySkhJVH0bowdV/SDirjY+sGowIq1VRrKSWyMUlKynlKoWvtDzePHVMQDKcTicsFguWLVvGp1ATdsy+yM3NlfWEchyHJ554Ai+99JLXNrx5dUtLS/06f0OGDOHjeIWwGepSrxfZ4CMUd972SSkjR47Ebbfdpnh9XwQ6MbR79+4YMmQIAHjY462i1/nz5yWL3zDi4uIwcOBAr5W3WrVqhdGjR7st8zX4iQfo++67j//bZrMhKSmJP4/Ca+fxxx+XbE8oqG+55RaMGDECH3/8sVcbnE4n781W8op10qRJmDx5steHG/EDZElJiUd2BjWoW7cu/zd7oAuVGGStkZrEN2PGDEW/rVu3LsaPHy/7faDCiD2kSzkYJk6c6JHaUi70QM23HMd0ypDEYGlWnU4nH5rBjqfw/gsk3CFQz/ioUaMUF10htIGEs8r47KIuD17CAcOoYgRSgic/Px933HGHW0euVCAKvYD+Ih5AnU6nxyxkf1L0yU2+BK4c723btnlt448//pD9buTIkXzGBnHZVaDKq/zyyy+7LevcuTMv1oSTxpi9YtikN+Frf7nKhIGknVKLiIiIgGaMCydLitMuyb0N4DiOn2wZDBaLxeNBxpfAEH8vFIJ6MWzYMNxyyy0A/BusKysrZY+p+NxNnTrV5xsbJYgrowrvR5YhYvHixfyyQPMHhwPBTuIV3hPCPj2YscWbcDaKI36E+6kByz4lFVIUrHD2h2AnlRPqQsJZbRRMDgS8Z97QC5vNBpfLJTl5RxhrKTcbePLkyW6f5V7/K8kXLS6b+uGHH3rM4JZKsC+HXEEW4MpAICf0/R1s/vGPf3gse/vtt9GpUye3ZUKhKM6VKtXxsjzUwpnQwslmQoQ5jfXGZrMF5HF2Op2yXhe59oSTkYDgYrjFYp2dA6VefS1T/SnBH08ix3Gyb1DE4TwFBQUAghdz4n5FGI5z5MgRAHBLbaZ21oFQIpC3j2IPL8tvn5iYqIpNLBwsUOEsTL2pBnl5eZoXVBEj7JfZ/cZy6PsrnL3lx/aFP2MfoT0knFXGV4wz+0ZYyalUFLOlVsfnC/Y0LZzBzzpL4WtCKYHQunVrdOvWTdF2lMw2Fg/SSkouixHGDn/77bd8h3/11Ve7redrlrcwRjCQPKg9e/bkwwSEXnJvHlYp7yUTlULh7Eug/vDDD5gxY4airAxqEBkZGbBwFqY0VCpKxRNQA51Bz3EcGjRo4DbgsfzHcpkYxCFMeg/iTNAy/PFyHT58WDaWWO4tBpuoGSgHDhxw++xLgEmVjA4GNokrFFi5cqXkco7jZO8FcWxzv379UK9ePbcHqmA8zmwskLs+hIjzpQPA//73v4C3LYXDzzk3WiM8zkruReH6/vZbUjm8/SEyMhLJycno3bs3Zs2aFVRbBAlnw4iwWnkR5RCJDrXS6fiiuLjYoySwVLJ1KU+VOI+zFGyg9xZryhAPqp07d/b5GzHCGOhNmzbh6NGjSE9P95hU6I/g8FVMQixmAPcQEKHX+csvv+Q9pOLJb0rPufg4ZWRkuGVPsFgsGDp0qKLUbGoIP7vdHnCoxqZNm/hrS3yNSLUXSMEYb7C3Ei+//DKef/55PkZfaciR3mmcvMWx+mLWrFmy8dNyAieY4hV79+7F5s2b3Zbp/co/HOKni4uLee884O5Ukar45i1EzV/YPciuG6m+jiF+uwZcEYp9+/ZVxR5/90rJ/dmnTx+/7WBOD39jx4XrC9P1KSGYTCHDhg3D999/jy+++AJPP/005W1WARLOKmPxFarBvhOsJ17fpmI6HV+I018JBQt7PcQmd2RkZPC5lqVes3fv3t3tM8vVKuw4vXlQhFx11VUYPHiwwr2oQjyQ5OXlIT8/32PAFoeFiPGnQxSm5JNC/PaAFSYJFOGxE+a9DoTi4uKgfs8I1OMMXHlFLT4nUu1t3749oG1IwV2u4AlUhQhs3LgRPXv29Lq+GG8DsziG3V+UpBDTQogGM09ByBNPPOGxTHgMhenKgvWmhTOrVq1yS3N2zTXXeF1fLJzV8DgrQa60fN++fdG4ceOAbRAinEtSv359DBgwwOv6vvrx2NjYgFJYSrWvRKQLnQPt27f3a1tKY5ylUlAaNYcqnCHhrDZKCqAAsAqFs2gA9JZRQG3EIlY4A1oqHdvEiRMBwG2WMQCMHj3aY7Bn3kShx3fJkiUYPny4T7uEVeWUIuWBKSsr8zgfrF2p9QH3Y+JLnPialHfttdd6/d5fhELclwhnMZBNmjTR9PVcoB7nFi1a4IYbbpD8Tqo94UQyLRBPZhMiFNoMb6FK/hZDEKNEFMvFuweDWsJZ6vwJ90n4t9CjSrhz9OhRt2Pp7wRWJb+Rgwlnf1Ikitm0aZNqITjC/Rg7dizuu+8+r29FvI0fzZs3R4cOHfw+Nv/+97/5Bxl/hbNwvGzQoIFf2/X11pa9oZWKow62wivhCQlnlVEa4ywU2BGip0kloQ1qIc4IITdgi/NGOhwOj4kT4t8uWrQIABAdHc0vk3tdPGzYMF6IcBzHC2dxyjBvNG/e3GPZxYsXPexin+UmLS5dupT/WxynqYRBgwbxf3uLV7/uuusAeMZgixF20DfffLPkcilYJblbbrlF8lWft1ev/hCox7moqEhywGncuLEhnb23BxEmnIW5yL29uWDnhnlevVUJk+ovAvUmiwsd+YvwepcqrhEMwnPqb474cIelZWSwNJWBhJsE6nG+8cYb3T4bPflVTJzgHsrIyEB8fLzXtxXeJqW//fbbfClqf7jmmmv4sBR/RTfr65599lm3+ThKiIiI8JqCLj09HUuXLkVsbCy++uort3HCW18qFZpJ+IaEs9oouZksFreQDvEvbDrFOAOenaPc7F1h0vmioiK4XC63J2gWL3r69GnJQV88MIixWCz8q/Ljx4/zwplVYlOCVEcmVQqcHfdz585JzmYXTsaTqtblK9uAeKKfXPq0J554AmvWrPEoZStGbiD0NahaLBasWbMGQ4YMkTw2aoiXYcOGISsrC0899ZTigjGM7OxsyTjrli1baj5oSwkKbw9J7HpMSkrCmjVrZCdzMdjxvu6667BmzRq88847sutKHYNAhXNycrLPdebMmeOxjMV3s0G2Xbt2fIjVgQMHMHv27IDzuzOE+6RVBcMFCxZgz549mrStJeJ7kT20+DtRXCrGWanAE6dnFN6DUvcLc4ywkvdaw66f2rVrBxTzK5yQHREREfQcBX+zarDzICxm4g8svIMVeRK3zR7k69SpI/t2h1AHEs4qI+V5lVuPwXGcbhMCxbDKbQy5SXk///wz//fnn3+O7OxsSeE8ffp0yfzHvXv39mpHZWUlYmJiAFR5wd99912sXLnSr6d6qWMYFRXl0ekLP0vNBhfC9tvhcCAjIwMVFRV+e4GCmdQFuHuChLb7U+JVaqDxNfFRCczDmZWVhWnTpvntoZfKgW2z2Uzn7RLncfU3r6owiw57A8NKyYtFU3x8vCJPoXhOgbBtb0jFxrNl7LgfPHiQF0b/+Mc/sH79er9KBEvxxhtv8H9LxasHG+v8559/YsGCBfjXv/7llg1n3bp1QbWrNocOHfLIGqQ0i4wvfM6x8ULnzp352PPKyko3m6S8s6xPCVQI+gsbVwOdJ8LuX19zXPxtT/y3kvWDxdd9LtyWnENDLi6d8A0JZ5VRWnIbuNLJHTp82JBXl1dddRUvVhkOh8OtXDBjyZIl/N8sM4TwKdvpdPJpi9ggLHzC9xV+IkzVJjwWSiZJMaTST9WoUcPjfATyBM4GYiWZKLw9BIkfVHwxcuRIt8k1TqdTdrLNq6++KtuOlEckmHRR7JiKX+crzdSxdu1aANKDia/QD5avVk/8jbkX75fFYuHDjtg9x46huDR4+/btcfDgQZ/bkCq7qyTMy5vw0KL8rriPYbRs2dLtc7DZF4TiTpib+pVXXjHVg9jMmTM95hzY7XbJ4+RvXyUlnJWe0/j4eH4OS2FhIb/thIQEbNmyxW3d7t2788JZ6gFOC/w9FuLjwCZW+jvpXI5AQzXUQDzGiG0RziuSmkMwZ84cPProo6rZU90g4awySp74LcJ1XS7d88EyIiIiPMIOLl265DW7gByLFy/m46Xmz58PwD0Hsq+Z1cIsHUJBEGy8d0xMjFePs1JYbufDhw/79NR6i8u+//77/dquuJBLbm6u5IMNAHTs2NFrO2py+PBhAJ6eV6WxyUzkSz1I+JpsGGwcL+D/NXDu3DlJ77gcUg9P06ZNAwCkpKRgzpw5/Hk9KqqGpvRhUSofua9qhnfeeSe6d++O2rVrA6iqEggAGzZsAACfsZfC+H8lPPXUU3j44Yf5z8JBXHztBPNKWTyp8fPPP3f7LMziYUY2bdqEyZMn46233uKvEyksFgtSU1M90lkKUSOrxm+//cbfywMHDvT4Xtife3v7cs899+Cmm24KyAYxgeyLMM75nnvuwZo1a3DvvfeqYo8QPTzOwrdWjHnz5uHxxx/H0KFD3ZYPGzYMH3zwgWxbXbp08aglQCiHhLPKKE5Hx3/k3F6dtm3bVivTPLDZbB7eJ7kJW/7AOghhlgJfAzoTzvHx8XjllVeC2r6QESNG+ByQpTx3Ypi42bp1q9cQiYSEBNlsHYD/HmeLxQKn04nTp0+D4zh8/fXXHt7Ijz76iBdAcqgtnFmOXnEIiNPpRFlZGV+mNjc3F0VFRV4zVjB++OEHLFy40MPjfOnSJY9zKI7HDJQFCxbg3//+t8/1xFUsfTFo0CC8+eabkt/l5eWhRYsWfD8hftjwlqpKSsQAV171X3vttW4Tfl555RXMmzcPzZo1wwsvvICxY8eiSZMm+Prrr92qWzJbXC4XWrdujccffxzNmzf36MtYhcqKigpFD0m9e/d2yxs7Y8YMvk1xZblAhXNlZaXHpGNx7vn8/PyAihnpyfHjx9G6dWufE6Lffvtt2bdF4vEnUOFcXl7On19hdUdGRkYGL5i99S0RERGqpUNzXW6HPfT5Ijs7W3LCuFr4m1VD7s2LUtLS0jwm8zmdTgwcOJAP+2LYbDa/JyASyiHhrDL+xJhJTeRQK/5KCTabDT/99JPbsi+++MKt9K03QSbn+VSS0ko8SDLhLCewxo0b57NNKWJiYuByubBv3z5eIIu3feDAAZ/C7sSJEwDcywILPS2jRo0CIJ3ZIxisVis+++wzTJ8+XXaCZVpammy1O2E7asImk4lj7V5++WXceuutGDZsGIYOHYpJkyZhzJgxGDt2LF8YRuhNFno9LBYLEhMTeY8zyzM9btw4D49KsLD7LikpyWduXMD/lE42m032IalOnTqwWq18m+Jc6s2bN5ed/CT27v3888+orKzk90f4hqZly5ZIT09H48aN8d5776F79+5ug32rVq34yWdffPEFgKp74ciRI6hTpw7i4+M9ipgAVcdu1KhRXic8AsCkSZMkvWzMVnERiEAEVmlpKUaMGIFVq1a5LWfXp5ARI0b43b5STp06pejhUAq2395ihYXpDWvWrCk7TgQTqiFkwYIFkg8yLO9xREQEf615m6gXTMy1GJa2VVi63RdahB4Fup2rrrqKf/BUCyVinMp1qw8JZ7XxMTmQc1vVvVNJ79hR1xzOERERsvkk2cx7b4JMOEhPnjyZ/1tJRyl+Fe9yuWQ74A8++EA2M4Uv2DF+7LHHeC+N2L4XX3zRZ4f2448/eiwTZjBgHafaZX6lBK/SUudCmPBXCxa24I8gZ4Our/hdm82GP/74A6NHj5YVrGoWQ1GCmjPTLaKsOuIHTSaqpe6jxMREvshBmzZtMHfuXOzbtw8XLlwIyGZx1gZW0IeFCEllqPjmm2/gcDjcss8IYXMdpIoxAFceQqxWK5/jt0+fPgEdY7n0lnpzzz33eJ1j4A12PLw9dCsV/WoKValwKRaHLkyv6K0PULOSIWtHKmRBjkAq0GqFxWJRrRgMUDU3IiUlxed6cg4uInBIOKuMoifcy+tYLBY3Id2pc+egX+f4g81mQ82aNSXj5bp06eJXjkd/46XEnbJUJUL2Sq5JkyaKPQfp6el4/PHHUatWLXz77bduMcKsDY7jPI6zL4+i1OtBob1skpy3fL3C3JpKkRqUdu7c6Xc74kl8TDAFEwMZCBkZGXj88ce9rmOz2fg0gGwSIcNXzmul+Lvfak4uY6mw5K45q9XqEdvOGDRoEOrXrw/gyoOrxWKRjL9WIkTFsdjsN+fPn8fevXuxY8cOj9988sknXttk+yV3zNjkX6vVyt9XDRo0CEg4a5XWLhDEbw6Uwq5F8QRxYV/CQt2UFEBRw+Pcp08f2etzzZo1bqEBenmcXRyHtLQ0v1L0jR49OqCy2v6i9hs9JehZ74Fwh4SzylgVpqPjMbAcptVqxU8//eQRD+gNufhLf/JqxsbGenTKUsI5kFerr7zyCgYOHIglS5YgNjbWzeOxd+9eAFXeUl9xcvfccw8ef/xxPo1ehw4dPNYR2ssGNjmP84IFCySrOvnCV4estLSz+HUd++xv7mWGUKg9++yzAbUhh/C4vv/++27fGTVYqBkvaLfbfZ7XiIgISeFSUVGB66+/Hl27duW/P3/+vKRXKRDBwsTu33//DSCw64Ptm1A4CzOHsNzp9evXh9VqxZo1a1CrVq2AhLOS7CN64U+ea+G5YSEe4vPNQpWAK2+3fKVBVCPGuU+fPujZs6ebPVar1ec8Cjl71Hpbw/mR2Wb69OmYPXu2KttVgl4hIYFgZtu8UVBQgNGjR6Nt27Zo166dZNiYUZBw1gC/smpob44sgSSRF86QF+LP5CmpPL3CdHQMNWIShQNJSUkJCgsL8fDDDyMmJkbSo84GseTkZBw7dgx//vknAOmcl2wS4OjRo/ljKRd/l5SU5HfuX2a/N5QWHxAPOMzT+PLLL0vm9S0qKuJjkn1x1VVXqVqBSnicxLGqzOOsludZKRaLxSN9WqAcOnRI0uMsLExit9sxYsQIvjgOO0ccx6F+/fq44447+Im9cXFxkhMclU6iEsLi6MV9mD/nl2UJEqbEEj7wsKwGwmtbWKjonXfeCXginzh8RFxcKNA4ZLURimIm/sUPZ+3atXP7/MYbb/j0nqpRcjsxMREOh8Pt+kxMTMSAAQMk1/eWflPtUA2l+zJy5Ei+z77xxhs9qiL6g9z++ZvHmfCPhx9+GBkZGTh06BD27NnjcT8YCQlnlQkkq4ZRBPJ6Sc7zJhc+IJX9QEo4//XXXx6eCTXihcWvvNnrUHFHx84D84bZbDY+BZ3wd0Luu+8+AFWigMWmCzMIqIGvc6T04YK188gjj+D+++93+53Uq/clS5bwMcmMDz/8kI9J1RJxeIaQXr16AQj+vvH39/7mcfYFuy6F94FUeBTLn8ti8NmchLNnz/IPqy+99JKHZ/j555/Hf//7X7/tql+/PoYPHx5QSkoGq2omJyak7iVhv/n9998HXKVQfI6uvvpqtzjXQMKctIaJaLEj484773T73LZtW5+FstQIjYiMjITdbncTzhcvXpR0tCxevNjtAUnKHrU8zi6OC+ge7NWrFx555JGAt/vee+/xJdDlIOGsLpcuXcKGDRv4txxRUVEemUOMhISzyliUPGELYpzBcWjfrp3iV+5q4u2VuBTeMhvIvTIVXuzMkyhXGY7lBgbgV6ltXwjPB+t45To6lmrOarXyRRScTqeHdzAiIoKPtYuMjOT/VrsDlRoohOmqlHpBmV033ngjRowYwachA6oqq8nluq6srERGRgacTie+/fZbPke3FP6+wZCL+ZbKT8xgsel6Zp8B1BfO7HwoqUKZkZGB9evXA7iy30JPvJQQrV27ttd4eznYmx9h/lvGyy+/7Hd7ShF6nNlnX5w5c0ZyuVhcvvjii/zf7777boAWagcLixETyBtBNWKc//77b6xfv95D8Eq9MfOV4UIuVj8QiouLUVBQoEpb/pCWluYxR0QMCWf/cDgc6NGjB/9PPDn/xIkTSE5Oxp133omuXbti2rRpKCkpMchaT0g4q4wF/s3A5wAcOHgwYA9LMAiFQNOmTXkPr7hIBxO/7DXhmjVrPDxjcrmLxa9op02bJlkZLiUlBb179+ZnCas1SAs77ri4OH4wkvM4C/NaC/Ps2u12t4pTr7/+utuDAEPN7AtSdgJVYSP9+vXzK82Q2C7xoCwuS8zWZ57M/fv3+9yGv4UF/C1FLnxgePDBB/Hpp5/69XshYnExffp0r+s7nU5NhDP7X/ggowStYr3Fcw369+/Pp4JU+jArJyJ8ZZ0QXqPCyn9yCMMdAGDlypUAqrztQiIiIvDSSy8B0CZUQ2yHv2zdulVyOYtbZ29ZlCD28Abifd63bx8OHz7s4dwIVMirRX5+Pv9G0GyQcPYPm82G7du38//E/a/D4cDOnTtx3333YdeuXYiNjXULZTMa/4MuCe/48aqMeZwB72VwtULcEX7zzTeorKz0GJQbN26MkydPehWFU6dOxbvvvov4+Hi3wUkYlzR8+HAAVblnpTrliIgIfPbZZ4HujiRWq5VP1SWc4OfrHDVr1gwjR47EV199BYfDgYULF7qFqTRt2pR/AmYerueff17SUxes/QAwa9YsvuOwWq1+l50W76/YK/fqq6/ihhtukP3d77//7rb8hhtu8GhT6PkUP1hlZmZ6VETzZ3a8uD1vuWwDQSqGXQjHcQEJB2/UrFmTb5OVOlZKIN5kJTDhzM7ttm3bMGPGDADS4qC4uNjNlvPnz2Pjxo2SbXsT+8zjzFLzKekPhdfb8uXL+QdYqRRk/j6Y+IM/FSWBqnRqQkeJnNOEhX/5275aOJ1Ot/7cV5iIFGp6nFPq10eMKG+8WTCzcDazbXKkpaUhLS2Nf2gcPXq0qYQzeZxVxu+S29qbJIvUBBypwe2uu+4C4D0fJPNGjx07Fj169OA9lVIxzlIllR0Oh+rCBHBP1VVRUcGfGzmPMyM5OZnPWepyuVBYWIi//vqL/z4qKoofqNkx69Gjh+qdFGtPOGj5W8UO8CxUotR7ygY98eAeGxvrUfmNnT+ptw9i73gwMYdaIJxkKVXlUm2PM1DldWHH11t4ihTeimUEysqVK3nhzGKpS0pK3M6n+MFWnJZQPBlPiDfhxTyl33//PQBl2TyEFTzF17dU+6GKuCS7N9SqHAhU3fvC4xro5GZV5/GY9DyG8vVlRlJSUtCoUSM+fHPdunVeK6rqDXmcVcbqo6PwVgBFb5YtW6ZovYiICHz00UdeJ4EkJSVhzZo12L59O3bu3MkLY6nOVipUQyodnRpYrVZ+4Lfb7fzxFh93qZhrJmqEtj7zzDO8p5TZq2aOXzmEHbO/Iguoinn94YcfFK/P9pkdJzZJjcFJTNRh51rOM7Bw4UJMmDABAIKa5a4GcvddSkqK5DWrVozz7bffjrZt2wJwf63u74xxNe+VQYMG4eeff8bff/+NxMRE2Gw2t4m5wodp8RsVceEVb95Fb7nSWfYFlpHDn4wgwqp6oQAL7VCaJcLfSnnicxCoqHM6nWjatCn/0BxoO6qlo1OlFW0wIo9zuPP2229j4sSJqKysRPPmzYMKzVMbOttq468YNlA4+0NaWpqijpMNgCyVmdQAL+Vx1ko4C20WblN8jnbu3OlxYzIvpHDA79WrF1q3bg3gigctEE+MUnxNZvQHcRviksnCY8IeqqQGhMzMTEnhzAZ4uRCMxMREtwqTcoiFkF6p59LT09GvXz/JgV4t4Txx4kR0794dwJXX2LGxsbIVPOVQ08P1wAMP8PZIedaFnuKoqCi8//77/BwE8YQdb32ft8p4rN9YsWIFAGDp0qUe62RnZ0tWI5w5c6bHsqFDhyqqqqYGbKJmx44dFa3PwlGUjBMzZ870WdpciJoe588//zzgoi4MNUM1QmWsJNShS5cu2L59O/bu3Yvly5f7FdqnNSScVcYCH52VidLRMVglMjVgHSV7xSL1elZPj7PQAxMVFSUb61teXs6XGxbamZSUJOspY79VMnEuUKSEs1re2hYtWrhlSpFKAycl0Hbu3Ck5GLI4YW8e+AkTJvCTuOR49NFHMXfuXL6jVDPDijdeeeUV3HjjjXA6nR65rdXOqgFcEYtS8wruvvtuj5zp3kId/K3cKUQYiuF0OvkHQVbaWBx607RpU/6csAJBDG/n3tvxs1gskveZcNlrr73G/y28j6UeXB966CHZ+RJq97nsTY6SGGBhpUPmXfdGRkaGX7H8aj5QORyOoCetq33PmDUggkI1qhcknFVGUfiFTMltvZk0aRIAz3yhwcCEM3uFKzWocRznMeFFy1ANJvKEsavsHEnFigoHqsLCQt5WOfu0fPgRZ18A1J0YJpwwOXfuXI/vly9f7rGMpfQSD4rC7CXe8OWhj4iIQIcOHXDNNdcA0HdQslqtyMvLw8SJE90mqH355ZeKC8L4sy2n0wmHw+EhukaNGoUhQ4a4PSRde+21sm3VqVPHr+wLQtjxZUUv2HXOHqilBCH7jVDMAnDLfe4PUoUyXnnlFQwbNoyv+Ll7927+uzfffNPtt3L2SXHkyJGAbJSDxe8ryQQi9NBfunRJ9b7D19wNvVG1cqAqrWgDhWpUL+hsq4xwMpoU4hhn5oFmr//1hL0eVjvNlsvl4ie0SA1g+/bt8xhw9fA4S8U4S6VEe+utt/i/Kysr8e233wKoSoEmhZrlmMVInRs1j1Pjxo29fn/o0CHJ5VKhGjExMUhPTw+oYp0UTNSzanZ6EBERwWdrEE6eVVtsAVXXZmVlJWw2m6zQE06ilCvZbrVaceTIEY84dH9JTU11q+DJBLM3T2qgeXWHDRvm9lmqkiJLkSicBMiQy9yhBG+x1oHgbe6HGPF51iJ9ZbAxziz0ZdCgQfz1F+hbHzUrBwIw7eRAonpBwlll/OkIXS4XXJc7lZqXCzvoCetQ1RRiSmPa8vPzUV5ejj///BMcx7m9IlYToT1Sr5Gltin2mObk5AC4UnxDjFapwQBpj7PaHlhvk4/khLXUOY6MjMQrr7yiml1ssPaVMSEQ5AZz4cOA1t46i8WC06dPSxYwEcLyH8vF+Pkj3OTo0qULWrduDZfL5ZEdRS5HO4N5hIXI/YaFn4gfNv19eGcT7LzFTYthcdlqewcDFeI1atQIuLS4HGpMOO/UqRPq16/PhyfNmjXLIze2nvbwmCCsUYhwv8wcqmFm20IVEs4qE+mrMIHgZispKcHmzZsBeKbr0gM2gBghnAFgzJgxePrpp7Fr1y5dPM4Oh8PD48yEs3ACmthjyoSNVKq+t956S9MMEVLCWe2Bf8GCBbLfyYUHbN++XfOiPXXr1vXI36w1QhGrtXCOiIiQrX4npGPHjnwZaymUtOELJnCEaSHZ9e4rdve9997zWCaXblDqegaueJxZeI5S/LkX2EPgzz//7Nc2fMFxHP+w7avve+yxx/i/nU4nvvvuO1VtkQrV8Fc4sZza7K1S//79fT48ebNHTa+6WSUgidPqBQlnlWE3kLdBV3iLsUlIsRp6LWXtuGyrmkJMWDzBF0ykrFq1SpPJV4D7K2ApjzOboOPN5j179gCQ9k63bt1al6wawJWYU7U7aW+FKeQGvdzcXCxatEhVO/RE7nwLj61w30ePHi2ZkzwYLBaL4gdmX3HjgHTOdH9scblcbqEa4jzlcpw4ccLjePbv3192O8L/hcs5jpPNLiL0zArDQ26//Xavtklte9WqVYp/owSn04lWrVohMjJScWrKpk2bwuFw4MSJEwAgWXwoENTw8FZUVCAnJwculyvoviacQzW0dGYQ5obOtgYE0nlZDegQtPA4y82O90ZlZSUiIiI0eWoXejwqKys9zgt7za2kOpeWAlkO4cMNK0uqhWdeiFAwqh0PahaU3J/CfY+Li3MrkqIGVqsVdrvdr3ADMez6SE9PD0p8MYEjfPMj9jx7Q5jPOSEhwae9YqHB3lTJnRdhrL3wvPTs2dOnbQytQqrYQ7/NZlMsnFlmIVZAZtSoUarawwhEtLLfVFZWBi0I1fY4mwmjJ14qhbzh6kPCWQMCEc4WA55YWaeo5tNyIB6Gbdu2afbELjwXBw4c8PievYJUEnbQsGFDdY1TgDAdnZo5nb0hfPUvlWkDqHp9ryQns1mRG8xZCjbAXTBqlY6OTQ4MFJYp5syZM0Hb53K53IQzuw6UPKidOXOGF43ehJLcNewrxEs4QTBQT59WD5ysHHtZWRnWr1+v6Ddika1Wjlqpscff/oIVAfrjjz/w0UcfBWWPmh5nM8tUM3ucSTirj3nPdghjsVjAeXvKlriQjbi4zeJxBrTz5ooH5Hnz5gG44i2Ii4vDzJkz+TLWzz77rGxbehVUECJ8ta3FZE6GMOzC2/ljE/V69OjhMyOHmZHzDArvQ+GAr4VwtlgssNvtAZ/PBQsW8BMHXS5XUPcQ2zf29gcAioqKeDt9sWfPHuTm5gLwXVpbqk0msFwuF7p06eJ1W8JcyGZAeG0sWbJE0W/EWUS8een9QXyNBiJahaXg2TkNFLWr45pVAppZnJrZtlDFEOH8+uuvo0OHDujYsSMmTJiA8vJynDhxAr169ULLli0xbtw41Wcb64m3/MxmemrWQjgraWvq1KkYPXq02zJWfUttxEJ+w4YNHusIBy2pvM5GIhwItewAIyIiEBsbC8C7x5BVvZNKRxdKKHl9zB6mAOCLL77AwoULVbXBarVi2bJlOHjwYEC/T0pK4h/mmNczGFs4jsPWrVv54kWZmZmKf79kyRJeIHkrH+5NOLNQDXYdAnD7m7F69WrFdumBMBZY6Vsp1WN/RfYI8bffULPan6qhGiYOjTCrOO3atavX/O9EYOg+8mVlZeGtt97C9u3bsW/fPjidTixatAj/+te/8Mgjj+Dvv/9GYmIiPv74Y71NUw0tO0U10WJyoBKPc0REhG6xs3KDgPD8mFkACoWGFg86DDaTHrhSElhMu3bt+HLYdrvdtIOFEpQM5k888YSmNlitVjdxHmxbwV4XwXoZ//rrLwDeK1vKhYcJBRZL/whIhzD88ccfAdmnFcIy5d7OAetz+vfvr9m9o0YBFGEb7du3D8qecJ4cKMSsfeHs2bMxYsQIo80IOwxRDA6HA2VlZXA4HCgtLUWDBg3wyy+/8F7IyZMnS1YsCxW8hmqYSFBrlcfZV0cpVexAK+TsCbUcnHrEOAsnUQKe4qZFixbo3LkzAGDHjh2mfuDwhRkmLKl1/Fq2bOmWRi4Q/vzzT750dKD3JgvRaNGihc915SYHulwunDt3jl/OqlRK8c477wRkZyAsXLiQn6BYWVHh1n8Iw1u85eRm4UGNGzfWbNKcGjHOQrp27RqsSdUixtnMYwihPrqnCUhNTcVjjz2Gxo0bIyYmBoMHD0b37t2RkJDAx+ilpaXJemLmzZvHx6k6HA4374QZcFRWwhUTg4vl5YiS6DCKOQ5lVityy8rgEhTUyBWEKnCVlbDpsF/l5eVISEhAcXGx1+OYn5+vuM3CwkJER0cjISEBNWrUkGzX6XTC5XJ5xPVpcS6Li4sRGxuL5ORkPvUcUFXMhG2PHQcpG5577jl+gpwR11pFRQUSEhJQUlLCH7P8/HzVRBc7t3a7HXFxccjJyYHdbkdCQoJHufLWrVvj0qVL/LEqKysz3f2nBG/XJvuewdaRuz6CoWbNmqq0m5ubi8jISLfz4c89C1Tt39GjR5GQkIB+/fohJyfHp23i+5ddq06nU/Y3bB2W8oxRVlYGm80GjuNQq1YtXogKrzcxwnvYn/0EqiYDOysrYVEYIuaoUQNnL11CzdxcrN+wAW3atEGzevVgy8nBxx9/jKZNmyIhIQEWi0XWJtbPVFRUIDo6GsXFxX6ff1/ntUaNGigtLXXr2yIiIgI+Tt72RwmlpaWIjIzk23D4cczFFAOwWyzI1Wl89AW7loGq+QDB9g3+3rOEcegunPPz87FixQqcOHECCQkJGDNmjF9FDqZPn86n5apZsyaSk5O1MjUg7FFRsFVUIDEqSrLSXO5lb3RSTAysgg4kSbAuV1mJSB32KzMzEwUFBUhMTPR5HJUeZ6fTieLiYj7XqtTvYmJi4HK5PMr1anEuL126hEuXLsFisbhtj4lp4MpxkLIhOTkZjz76KDp37qwoLZfa1KxZEwUFBahVqxZ/zJKTk1X19iYnJ8Nut/Ntnzt3DmlpaThw4AAvnNnkQYfDwR+rWrVqme7+U0JBQQFKS0tlbRdeJ2yd+vXro2fPnqrub0VFBRo1aoS//vorqHaZvQkJCW7t+NMma6Nhw4Zo3LgxkpOTkZKSgkOHDik6TgDQqlUr/hqSg13PMTExbutlZmai4rInNy0tDdu2beP3Qa6sd0pKit/3wWuvvYa77roLSUlJcEZFwaKwYqu1rAzRTid+//HHqte0JSVIiopC5GX7du/eDaDKcSC3/7m5uSgoKODTELJjwfZTKd7WtdvtiI6O5teJjo6Gy+Xy+/pidtlstqCuzZycHJSXl/Nt2P045mKyAVRwHH/cjSYqKoo/TvHx8ar0DaHYn1ZHdH/XunbtWjRr1gzJycmIjIzEyJEjsWnTJhQUFPCvsjIzM1UpI2sU3iYHXl5BL1O8Is7XqgYWi8VnLlOr1ao436ka9ki9evYnxrlnz56GiGbAPX2XFjHpwu0wkWy32xEZGSn5ilV4rVSnUI1GjRqpPqhZrVY0b94cffv2VaU9Ne5j4TlXUnRFvH1xKW0xSiYHtm7dWtH2Arn+GjZsGHDcLStWAsBnyN3333/PF05ifPDBBwCAIUOGwGKx4OTJk37b4Au1sliwtIzBhiCEc8ltIaHcFxL+o/vZbty4Mf7880+UlpaC4zisW7cO7du3x4ABA/hUPvPnz8fNN9+st2mq4TMdnQh/kvirCRMPalcOZNUQn3vuOcl1rFarW8ERYe5ctWGDpLcBgH3HMkaYCaHQ0HLCqVLhLDyOoRzX569wDqR0sS/UzF4AqCecA91PJZXmfFUO5DjOo7xzsBPUxKgxx0LuTjxy5AiAqvjrTz75xO2733//HUBVf2exWHivupqo1U+wYjFqVA40w3wCrQnlvpDwH92Fc69evTB69Gh069YN6enpcLlcmD59Ol566SW89tpraNmyJS5evIipU6fqbZqqyHZeUmJEY1vk2LJlCwD1Pc4MuTy/xcXFboUCYmJivKawCgY2SCqZbb5jxw5NbAgGOaGh1XZcLhcqKyvdcvHKCZdQ9rIEIpy1yOOsRlnj3r17A1BfOPu7v0pyXctl1RC+hapZs6bbdyNHjuT/njRpkl82SaGGuFTye5bWT84GhprZW8T7Fuh+svPTsWNHVe0JBvP6m0k4Vzf0ryEM4JlnnsEzzzzjtqx58+bYunWrEeaoTklJCc5kZsqKQfEtZtRN179/fyxbtkz1yoGM+vXrS64jrq7lcDg0Tc8ULunotIZ55w8ePMg/VAHAXXfdpfm29SbYNF1qwNIyquHVA9QrIhToNVdaWurzXpJrOyoqCna7XdLjfc0112DGjBk4efIkIiMjg/Zisodpf+/6hg0b4uzZswFvV2wDy8Ch9psuNbJqsPOYlJQUlC2q53E2kUANlcxMhPoYIpyrAyxcQREG3XRsoFU7HZ0vxJ2Mw+HQTLwqSeFm5k5PrzLbbFtOp9OtfLLVapX1OmlVwlhr4uPj0bRpU79+o2WxCrWEsxr3UDChGhUVFQELZ2GoBvvu/vvv578fOnQoAGDGjBlBC7FAj1O0KIQEuHJd9O7dGw0aNEBhYaFiG9h+sGqcaqC2x9lUMc4wb+VAMztfCPWhs60RXjsL8aChsS2+0MLj7M/EIjW8br7wFqphZuGsp8eZeYd69eqFYcOGAfAe0mDm4+aNBQsW4J///Kdfv9EqxlmNa595QdXwOGdnZ/N/KykxX79+fbz11lsA3AuByCEXBsLedgiPs9SDGYshDoZAY5zdevTL/YewnaSkJMTHx8v+XjzBuE2bNgC0zaMf6HWrpnBWy+Ns5lANonpBwlkj/HrKNkiAaFlyWy73KgBMmTLF7bOWoRr+eMBHjRqliQ3BoKfHmVUPVHrthqqXJSoqyu9rXosYZ7UmTh0/fhyAevcx28+pU6fim2++8bpuZGQknwVDSTVJbx5nVgDFG/fcc4/X75UQaFYNqd+wNzMs6403+4UV3Nj6SjOIKEXq+AfSd7BrSY23IVQ5kAg3KFRDI+r5kbrKqFtOi8qBSiYWiePmtPQ4+xOqIReTbSR6ZdUAqoolsFfNSkRiqArnQNDi2DPhrNa1r9Z9zOyJjIx0myQqBbsG6tatq6h6obd0dOwYWywW1KxZE61atfL4vdJQCF82BORxlrgGhELZZrN5Fc4NGzbkQ06UZPsJFDWuVbXubdUn1KramnqQcK5ekHDWgEaNGiE2NlbyO6kuzaibTou8wEq82OJXyuXl5ZqJMLmBOlQmB+ptW15enmIvaHUaLLQSzk6nU7VJfWpPDvRnXZYVw9dv5eKxxTHOS5culfz9wYMHFdsmR1lZmeoeZ8AzBERcelzoIGDiXYvwHzWFs5lCNcyWxzlUwv0I9SHhrAEWiwUuLze5xy1msHDWYnKgME+z3DqMYHOqKrEnVNEzxjkyMhKJiYmKPWHVabDQwjuoVjo6ht6TNcePH88XPMnJycHp06d92nD06FEA8gVQfB0PNY6V3W7H7t27ca3C9ZlAkhKAwr6L7cOpU6cAwMNbL0zXp1Z8uxgzTg6kPM5EuBHaqsKkeH3qFyxn+VeNuuXUnI3PUDJ4i9dRUzyIkdu3UPEW6Cmc69at6zFByxuh/lDiD2bO48xQO1TDF1OmTMGAAQP4z7/++qvP37Lqe0qyakih1j7m5eVhz5492Lhxo891WV9RUlLi8Z1QOLM5AnJx2MLJk1qGXpkpVEPNfstc/mb3ByOtw+gIc1F9Rj4dsVh8VA4UiyGDhZsWMc4sR6kUvirSqYmSUA0zo3c6OnE1SW9x39VNOGuVx1nN9oyksrLS5zXBJshJhWooqWTK9vGFF14IxlQ4nU7k5OTgzJkzvle+3Ffk5+dfWXT5f3GohvCzZzOc2/2spGBMIKjhcVZrcqDqHmcTOTkGDRrEZ5QhqhfVZ+TTEauPUA0GL+q0NsgHanbebJ+Eaa3k1vG1TE17zOxV9oae4pQdI6WDbageU39gx0KLBy21RYXeHmcxSvI4szhsuVANX8d58ODBABB0pVFfkx6FeLNJ7HH2tq7L5eLPkVahGlJvOwPZhlr9ptolt83U49hsNj4rSnXoC4krkHDWAIvVKutxFnZp/K1m0E1nVOyZ1OBqZDo6M2OEx1noXb1w4YJP28KNqVOn8n/n5eWhtLQUgPr7y17tq3Vug2nnmmuuCbqdysrKgLNqKA3VqFu3LgDPstz+kJCQwOdQVoI3MSx8s+YrP7S4v9UiRM2MMc6qPXSGyFtCIvwJz5HPYJRODjTa46ylcPZWCKCGRAUurUQYm6SoJFTD32pyeiCMQ5c6bmpviwnnQCpAhgtjxozh/544cSJmz56tWeowPYr/KIFN8gMCP6/R0dE+f8u+Z5MEGcICKN6uvb///jsg24Q0bNjQLzEn2ZdfXibMc61EOAtDIPSYHMiW+YuaoRrVIY8zUb0g4awBVl8xzgyDwwiMymYh5S3S6hjIddpSkwM7deqkiQ3BIPTQtWvXDh9++KGm2/KnAIoZBJ8eXLx4UbPKgVpOjPUHNSbLlpWV+XzgYg/r58+fd1suFM7e6NGjR0C2ibfF7FByrR8/dsxjmeNy35mbmwvgirdd6Ixg2TUY8+fP5ycj6pXHOViPc7CoXQDF+DtFGjPcw4R+kHDWAIvV6leMs1FoKZz97Sy1DtXw1n6tWrU02bYaCO22WCxo1KiRZttSKl6E61cHjh8/rmkeZzOgVpYZX9cE21+pUA0lD20pKSlYs2ZNwPYxG4XFVnxRLpFa8/Tp0wCu7M+OHTs8hHOzZs08fpeVlcVvV6sYZzGBbMOMoRpmDtQweiwn9KV6jHw649XjLByg2P8G3XRRUVGatW2WrBUsJtJbqEZKSgq+++47Xe1SinAykdYIxQvlcXZHK4+zVl5Hf9FLOMsJVuG1p/W17q/H2dvbQ2EWDSaGGd5Cq7R626CWUKU8zv6h5VhKmA8SzhpgVepx1nHilxRNmzbFF198Yci2xWg9WPqKcTZrx6dnVhClcabVjfbt22saqmEG1HrQVepx9lU5UEukxFxxURGWL18uuX7dpCSPZSkpKQCA2rVr88vEHmdfNpg5xtmMHmezTg789ttvkZCQYLQZhI5Q5UAN8DurhoEkJydr0q5ZPM5m8OYFg97p6ITi5amnnkLDhg1l169Xr55uthmJVoLOYrEoKlPti4SEBBQUFATVhloeZ1+/ZdthwpMhfGjT+p6VemDJz8+XLHACADUkHqrZftx4443YsmULBg4c6LdwNnNWDTVTG6oZqmHG/jw2NtZoEwidIbeSBvjKqsHPDBb/H0YoHUA++ugjANoJRLncxGYR9r5g9ushoMW5dK+++mq3bAtCOnbsWG280v5MmPQHtV7XC72egaJXqEZaWhoAICMjw+N3enqcxfm5vdktde6lvLr+xKxrJZwBdbIlmXVyIEGYAfI4a4DVYoFTSYyzwenotERp5808mlqLMPGAFiqduRZl0eUQCgpvA3rt2rXRtm1bze0xC1qFr4RbVg3A93Vap04dycl9/sbXB4OUx9nbNr05Qdhxa926tV+hN0xkq13tUUnaTSWoFaqhqnAOkT6bCH9IOGuAxUdn4TEp0AQDp9oo8bzExcXxHbTW5YLFA1qoCWc9UDpB6+uvv9bNJjPArh0tYpzViHONjo5WyaLgCfQ+FopOPYSzP3HA3jzOHMehT58+GDFiBA4cOODW70m1KbyvXC6XXxUMlWDGGOdwrRxIVF+qx7tWnQm1ktta4K8wZaV4CXf09DhLVQ4koNkxUUtUxMXFBd2GXjHOvmzQK1RD/MBi8XZ/+RDOwnAq4fmU6gO1Lrkd7sKZIMwACWcNsHh5ZSc1OTAcRYoSj7NwHb2Fc6h5nPW4RoSTA4krFBcXaxrjHCy33XYb7rnnnqDa6Nu3L/+3lqEa3n6nZ6hGsJUDWeETob0RERE++z2hyNZKOPsS70pQs3KgWnBVDarWHkEECglnDbD6mkksSjFWWFSkh1m6okQQCI+R1qEaoT45UA/hzLICkMfZnezsbLhcLtW9/mpNEGvfvj1uvfXWoNuYPHkyb1egBCOcOY7TxTspFVvub6gGQ9iO+EFISkQzB4GWWTWULAuknUAgjzMRKE6nE127dsXw4cONNsUDEs4a4C0dnfuKVZ1T0uUiHeGC0k5X2KFq7XEWd96h0pkb5XEm4eyJVjHOZkEo6gIlUOEsFFiGxDh7Wd9XXy6cpyHn7WV/C4+xVh5nNVDL46xqrvIQcXYQ6vDmm2+iXbt2RpshCQlnDfCVjk4cohERZvG9Sr3Hwg710KFDWpkDIHQ8zGL09DjrmdnA7Igf5Mycjk4t1HjrE6hw1vNthz/HvaSkBKWlpbLfC68Lp9OJU6dOuX1mHD16FACQdLmYCrvX1H6LsWzZMsybN89tmdExzmrBITznAxGeZGZmYtWqVZg2bZrRpkhCwlkDvMbQSUzCKS4u1sMs3VA6GAiPUbAFHPwlVIS0Wp4fJZSUlKCysjJkjo2WjBs3zu2zlpUDzSKcgxFL9evXd2vDX9jbDj2Oh2RRDpltLl++HDt37ZJtS3hdeHurdfDgQQDAQw89xNughcdZyr5AKCsrA6COcLbb7UG1IWpQvbYI0zJz5ky8/PLLpq0VYE6rQhyrwrgu1ilVVFRobZKu1KpVS9F6wmPUuHFjrcwBEPoxznp0IIcPH8Z7771HJbcB3H777WjVqhWAqutZC0Fn1lCNQM59sGEerICIXsLZI6tGgG0J7xXxcRN7owEgJiaGX1cLj7NaLFu2DIA6oRoAUFlZGbRNFKoRPjgcDvTo0YP/J3xLsnLlStSrVw/du3c30ELvhFeMgEnwVma0OmTVeOuttxR5GXxNpFGTUBXOesY4A0BkZCSFalyGHQN2bWqVAcEsxzqYtxtMOAcT7mG1WlUpQe6LiooKVFRUIEZiO/5e+97S+Hnr37TyOHfr1g1FgsnmgfZzt9xyC5YvXx60PXLe+IDbU6UVwmhsNhu2b98u+d2mTZvw3XffYfXq1SgvL0dhYSEmTZqEBQsW6GylPOZ83A1xLBYLSkpKvK3g9r9ZBk61SEpKQoMGDfz6zY4dOzSypopQFc56xjj37dsXY8aM0W17Zoc9tGg1YVKv1/VKCcb7KcxPHCh6HY+NGzfinXfecVsmLsGtFHEeZyFSwpnFS2uVbaJnz54eE6oCOZ7sDaBaHudQmYxNGM/s2bORmZmJkydPYtGiRbj++utNJZoBEs6acPLUKVy8eNHneqxTSkhI0Ngi8yEeZFq2bKnp9kJFKIvR0+PMQmxC9VipjXjQV/scREREmOpYBxNuEUyYB0OclUJrpPZT6fkQXhtyD7fePM4sTEftUA1vmT38bQdQ55pn4SmqYJKHTKJ6Q6EaGqA0not1SnEKY4LDCXGaohYtWmi6PTMJFH/QM8aZTWqlGOcqDhw4AACaTVrbs2cP7Ha7aTzOwYglNfZBr9CVkSNHok6dOsC2bfwy1jtwLhegINxE2HexeyUqKkp2HblQDbXvM7XSv6mZV1/VlHREtaJ///7o37+/0WZ4QKOjBvjq+MWxzWYZOPUkIyMDAwcO5D/rLWxDpSPXujCMEEpHJ41WHufevXtr0m6gBCPiunTpAiC4+1gvj7PkJEQWquFnW0J7xeFpwmPhcDjclmn1kCDO6GQGh4G/lRrlMH5PCKIKEs4aULdOHfkvJSaTWKqhd+/BBx/E448/DgB4+OGH+dharaAYZ98Iyx4TV4StVjHOej4UKSEY4XznnXcCCO6+0qoMtdx2hPvLrL4UQFpMOXtPnz7N/808zmLhrEU1Sinvtr+sXr1aLZPUi+fmOJocSJiC6qfYdMBnzLKoIzOLx8kohgwZgrS0NE23wXEcXnvtNU23oQV6F0BhIpFwzwigVR5n4XaMRg0hH6xwNtrjnJOTI/mbuLg4yeVKw5r0yqrx999/46effgq6nZSUFBWsqULViZAmuVeI6g0JZ6LaULNmTf7vUBGHeooqoceZYpzdj31hYaHq7ZtNOKtxzoNJYaaXx5lNyhRuh/UHcgKv0eUH+7p167otV/pAxYQzc6rk5eWhqKhI9X39/fffA7JPzE033aSWSao9EIVGj01UB2h01AKFMc6U0F0/xGVzQ0U4M/SeHGgWMWckwmOQm5urWaiGWY61GtcYqzgX6Pb1KAgjDtXgOI4XZXICzyJ4yJk4ceKV34nuFZaZZvHixW5earZf7M3a999/z7enJg888AA6dOgQdDtqTw5Uq781x51CVHdIOGuAt9yVnMzfhLaUlpaGnFhmrFmzxmPGvhYIPc5mEXNGIhaSah8T8cOc0Rj9lsGoUA2Xy3XFiSETRif3v9jeevXq8dsQPgSwyYFi1L6moqOjVXmzpqZw9lYQjCD0Qs3+loSzBrDXcbm5uV7Xo85EXxITE402wdRQjLM7TNQ0adJEkwwIS5cuVbW9YDF6sqLeHmd2PisrKngnRv369aV/Y7EgOjoayUlJAC733ZfvE+EDx2233cYvU1IZVY90dMHk5VaD3Nxc7Ny5M/iGqF8iAuCPP/5A+/bt0bZtWwBVaUDvv//+oNok4awBMdHRAIAL5897fim8+akj0A2bzVYtC834g3ASj9HeRzPAHiC0Cqkw2wPKhQsXDN3++fPnkZeXp/l2xLHlW7dtQxnzRonOCX/OLRaMGjUKXbt1478rKSnxEKlXX301nn32WURERLiJZbFwnjFjhpstamGz2VQpgFJcXKyWSQCAffv2qdoeQSjlkUcewY8//sjPT+jcuTM2bNgQVJs0OmqALTISgJdcwZc74wgVn+oJZSRd9hgRnhQWFiI7O5tCNUQcP34cgPrCecKECZq0GyjRlx/4jW5Dr3R0zKuamZmJLVu3AqgSmtkSDxBSNjkcDo97JSIiAldddRUiIiJgt9vd1hWiajU9AVar1WNbgRzP1NRUtUwCAPz8889Bt2Gux0wilGjUqJHb52DfrpFw1hBhxylFXFwcRt56q07WVG/YQwx5neX58ccfsWrVKhLOlxFnKFD7mLDO3CzHWg0xJ846YUa8FR9xcRx+XrvWI5+zVWLdqKgo2Qw0bNmpU6cASJfcFv6vFuJQjUA9zgkJCVizZo1aZqkT+sFxlI6O8JtGjRrhjz/+gMVigd1ux6uvvop27doF1SYJZw05fOSIxzJxNxYjmMhBaAeFICjHbCEEZiHc8zgHa8fQoUPx0ksvBfz75s2bq2KHL7xVKOQuL3eJ/hfbVLt2bbdiJmLYuS0pKXFrR2iD3G+DQRwiosU2AkFuciRBaM3777+Pd955B1lZWUhNTcXu3bvxzjvvBNUmxQpoSIvLAwFhHtgg8sEHHxhsiXnRYiJcOBDuwjnY15csbjdQ6tWrx4fFaInVakVlZaVksRMmhk+fOYNEQQVY8TkSTqT1dv4qKioAeApH5oHVQjjrkZnECDhQOjrCP5xOJx5++GF8+eWXqrZL7jeNaNasGZIvpyZyg7x5hiLMlEC4M3ToUPTo0QOAecScmVD7mJjtGHfo0AHTp083bPt6PUhERETgxx9/lPzOyd5M+ajuyoSzr4fMyspKAJ4eZy1DNdSIcTYt4bQvhOZERETg1KlT/H2oFuRx1oiIiAj+tZ8YuvWNI6wGEZVJS0tDjRo1UFxcTMdJB7QST4FSo0YNjBw50rDt63UcWNyxFCzMgTk9oqOjUV5e7nE/WK1WPuzO273C5rmIxaxWDwnh7HEmiEBo3rw5+vbtixEjRiA2NpZf/o9//CPgNkk4a4ReyfwJ/zCLSDErVDlQHrWPCUu9Rse6Cr0qKa5YsUL2u82bN7vZwP8vUQyHc7l89vGsGIlYOJ89e9atfbUIa+HMceR0IvymRYsWaNGiBVwuF4qKilRpk4SzRnAch/LycukvaaDUlfr16/M5akk4e0fJ6+fqitrHpOBy5gY61lWY4d5kMc7iiX9S54i7vJ7c+evQoQMiZVKTMuGs9j6LJwfSRF+iuvPUU08BuJKbvFatWkG3aXxPFaYcPXoUf0kkfaduTH+EgxOJFHmEb0noOAGrV6/GsmXL+M9qixxvoqw6otdx6Nmzp891xIJTKlQDl9/OyF0XNpuNF7HiTBfx8fGS7QaLVPVFo6+vqVOnqtIOjZ1EIOzbtw9du3ZFhw4d0KFDB3Tv3h379+8Pqk0SzkTYIxzYzpw5Y6Al5kZYdczowdYMWK1Wt9zGapekZsfYDJ5WM6BXqEZycrLPdX755Re3z1KTA10+wpqEIlYcqnHjjTdKthss5eXlOC+oWGsGjzOLK1UlhIT6JcJPpk+fjtdeew2nTp3CqVOnMHfuXNx9991BtUk9tt6YoCOrbggHp/z8fAMtMTcRERGS1dCIKsSevGCpXbs2AHpIYej1ACHcTv369b2uK/dWwGKxAJfDmuSKe9hsNl4wi68dFsKh9j5Llco2+vpiD0QFoqIyBKEHJSUlGDBgAP+5f//+fH71QCHhbAA0TOqL0QNHqMDiIynG2Z1JkyZp0m7r1q0B0PXJ0MvjzMqC9+rVC9ddd52i34jT01mtVnAcB4fDIWuvcKKeXB5ntWnYsKHbZzN4nFu0aAEAuOeee4JriCYHEgHQvHlzPPfcczh58iROnjyJ559/ni+2FCgknImwR21PYbginFhEYu4Ke/bsAaBNzl0t2g1V9LrmbrnlFgBAXFycciHmJY+zXAgPe4MDePZB7DeLFi1SbLcS4uPjeW+20FYjadmyJQCok9GA+iXCTz755BPk5ORg5MiRGDVqFHJzc/HJJ58E1SZl1dAZ45//qx9sBjvhHalyvcSVuHithLPRwsYs6HU8kpKSsGbNGthXrXITYgkJCR7hBHwcuoTH2eVDOAsnB4rje5nHmVUWVAupyYEEUZ1JTEzEW2+9pWqb5OrQiOsFMTUe0EBpGP379zfaBNPCYjIpxlkfmHgij3MVak++VILwKve2ffH9UFJSgvLycjidTq8eZ7nJgVqdc5YZp7S0FIA5QjXUgkpuE4EwaNAgtwfi/Px8fnJuoBjSYxcUFGD06NFo27Yt2rVrh82bNyMvLw+DBg1Cq1atMGjQoJCfxJWQmMjH0rkRRh0ZEV6wrBoU4+yOVvmWjRCKZsZoD7yUmJWbHJiXl4cjR47A4XAEFKqh1T6yfbh06ZIm7RNEqJGbm4uEhAT+c2JiIrKzs4Nq0xDh/PDDDyMjIwOHDh3Cnj170K5dO8yZMwcDBw7E0aNHMXDgQMyZM8cI01TDejkGTgqSJMZBglAeq9XKD/R0nK7Qpk0bAECdOnVUbddooWg2jAgxsEVGonevXgC8x+BKnaNatWph//79vHdXzN69e7F+/XoA8vv28MMP+2uyIpi94eRxJqcTEQhWqxWnT5/mP586dSroPlf3GOdLly5hw4YN+OyzzwAAUVFRiIqKwooVK/Dbb78BACZPnoz+/fvjpZde0ts81bBaraioqIDDbodNNFmD0Jf09HT89ddfRpthelhMJoVquMO8FWofk7AUN0FgVKnoBpczUUhVemXnyG63uy1PT09HrNOJ49u24fjx45gwYYLHby9cuMBXLBWHajCEecLVRCjUw+peDqd9IXThhRdewDXXXIN+/fqB4zj8/vvvmDdvXlBt6u5xPnHiBJKTk3HnnXeia9eumDZtGkpKSnDhwgU0aNAAAJCSksJ3OKGK5bI3SXLyB938unLNNdegc+fORptheiiPszQjRoww2oRqQb169QzZrs1LyAx7qCkrK3NbbrFYwPkh9OUeCrR6WFi7di2A8HooC589IfQkIyMDO3fuxLhx4zBhwgTs2LEj6Bhn3T3ODocDO3fuxNtvv41evXrh4Ycf9gjLsFgssgP3vHnz+KcFh8OBnJwczW32B0dlJSxlZVUzrmNikFVYiDqCjrnUYoEdQK6oIxbCVVbCZqL9CvV48z59+qBPnz7IyclBREQEEhISTHfdGIXw3Obn5+PMmTNIT09HeXk5HaPLWCwWza6ZhIQEVFZWqt52KN6zLpcLCQkJKC4u1uXaY301ALgEnt/U1FRcuHABuWVlsNSqBZfDgTP5+UgS9NllVivsqDp/VqtV0l72piInJwe1atXi/xZ+7+99puS8JiQkYM2aNRg6dCjveTb6XmbHIldwzP2lzGJBkcuFXJONj2oRivesmTl16hQSEhJQu3ZtJCUlITY2FsuXL8fhw4fx4IMPIioqKuC2dRfOaWlpSEtLQ6/LcWWjR4/GnDlzUL9+fZw7dw4NGjTAuXPnZL0P06dPx/Tp0wEANWvWVFQ+VU/sUVGwxMSA4zhYy8pgKytDkiAp/RmOQw0ASV5e0XGVlYg02X6Z7TgHitPpREFBQdjsjxqwY9GwYUMUFBTAbreb8t4yioqKCs2umYKCAmzbtg3jx49Xve1QO3+RkZEoKChAXFycLrazvhoArAIxd123bvh26VIkxcQg2umEtawMltJStz47x2JBhMuFgoICREZGStrLJpUmJye7/S38Xu633vC1vnBbVqsVFovF8Gth3Lhx+OCDD5AkOOb+EuNyId5qRVJUlOnGR7Uw+jyFE2PHjsWyZctQu3Zt7N69G2PGjMH//d//Yc+ePbj//vvx0UcfBdy27sI5JSUFjRo1wuHDh9GmTRusW7cO7du3R/v27TF//nzMmjUL8+fPx80336y3aarCPOZGxe0R0tx2223o1KmT0WaYEjb5jbJquJOWloaPP/5Ys/Ypz3gVRqflq1OnDoqKiviUbkKbxBmSLBYLXJfDIOQq4vXo0QOZmZlet6nH+GCGe5nFcpeWliL2cql5gtCSsrIyvpLmggULcNddd+HRRx+Fy+VCly5dgmrbp3C+cOECnnjiCZw9exY//PADDhw4gM2bN2Pq1KkBb/Ttt9/GxIkTUVlZiebNm+PTTz+Fy+XC2LFj8fHHH6NJkyZYvHhxwO2biWPHj6Nlq1b8Z4rTMpZGjRqhUaNGRpthStgAW1JSYorB1kykpqYabULYY3SWkRbNm6N1mzbgOI6PDWY2iTOqWK1WOC+vk5WVJdlenz59cOTIEa/bDOZ1cSjBzukff/yBQaNGBdQGV9WQekYRYY0wvv+XX37B7NmzAajzgO5TOE+ZMgV33nknXnjhBQBA69atMW7cuKCEc5cuXbB9+3aP5evWrQu4TbMino0NUDo6wtwYHQ9Z3aCHlCqMzmvNBlpWTluI2ONstVrhuLyOXMaMM2fOYM2aNZg5c6bk93PnzkXbtm2DtNo3Zri+2MR/gtCL66+/HmPHjkWDBg2Qn5+P66+/HgBw7ty5oB9YfUrv3NxcjB07llfpNpvN8A4ulCgsLHRfEEaznInwJCYmxhSDbXWBwrmqMNLjXL9+faSkpPCfmXg+e/YsOnTogObNm7utn5eXx3ua5cbDH374AYB8ZosOHTpoPpaaJauGKuFxJtkXIjR44403MHLkSDRt2hQbN25E5OW0wOfPn+cdwYHi0+McGxuLixcv8p3Zn3/+idoUo6QYyY6LRAlhYhwOBwlnHTEqDZvZMKIACuOGG25w+2yxWPgHmiiJPPzHjh9H0mWvVdeuXSXbZPeQlvHx1Q3qlQilWCwWyUnXcverP/gUzq+99hpGjBiBY8eOoW/fvsjJycGSJUuC3nB1hZ6ZCbPCJvBkZWWRcNaJxx9/HC1btjTaDFOwaNEio03gsVqtfHowKa8wE9W1a9dG69atJdto0qQJDh06hIMHD2pnqA/M4nFWg/DZEyLU8Rmq0a1bN6xfvx5//PEHPvjgA+zfv5+yEgQJSRLCjNSsWZP/m4SzPgwcOBBNmjQx2gxT4K3ktd5YLBZkZ2cD8C4+XS4XbDZp/xObB8QqEuoRzwxUpX4TElb3cjjtCxGy+PQ4f/75526fd+7cCQC44447tLGIIAjDCavBlggpzHDtWa1WuC6HjrgkhHO9evWAwkI4HA7ZOGW2/NixYwCqYi71gKXgysvLA2CO46kW4bMnhF58//33GDZsmKrpLn0K523btvF/l5eXY926dejWrRsJZwX06NGDMhQQIUk4DbZEaFBRUQHAHNeexWKB9bLwlfI4WywWcKjKFSsnnFm2jfj4eM9J4hpSWloKoKoSXTiFahBEIHz99deYOXMmRo0ahbvuukuVNz8+hfPbb7/t9rmgoECTKlfhSFRUlOdTDnVkRAhgBvFCEEYhLILSrGlTj++ZcAbks2qwGGmO4zBw4EAtzJSkuLgYwBVPd1jdy+G0L4QuLFiwAIWFhVi4cCGmTJkCi8WCO++8ExMmTEBcXFxAbfrtu46NjcWJEycC2lh1oyA/n44VEZKE1WBLhATt2rUDYI5rz2KxIPZyzH/N2FiP74ViWk44szkDRUVFuqZwZVlamIA2G4WXLhltAlHNiI+Px+jRozF+/HicO3cOy5YtQ7du3Twcw0rxKZxvuukmjBgxAiNGjMDw4cPRpk0b3HrrrQFtrLqRX1BgtAkEERBmEC9E9SI+Pt5oE3gsFgvOeCmXnZyc7Laur3XkJhBqwYABAwBcyZJjtns577In3l8o7KT6cObMGQwYMADt27dHhw4d8Oabbwbc1nfffYdbb70V/fv3h91ux9atW/HDDz9gz549mDt3bkBt+rybH3vssSsr22xo0qQJ0tLSAtpYdaNAQjjTrU8QBOHJDTfcgC1btphC6JWUlHj12CqZaNRU4JVWc2KSL9jx++KLLzBkyBBTHE8A6NevH5CdHZQANseeEFpjs9kwd+5cdOvWDUVFRejevTsGDRqE9u3b+93Wt99+i0ceeQTXXXed2/KaNWsGnGPdp3Du169fQA0TVRNHJDFJR0YQcly4cMFoE4hqRps2bYw2gceXuGNCuEWLFora0zNUg22LZdUwC9dffz3yFi0CR5UyCR80aNCAL9MeFxeHdu3aISsrKyDhPH/+fNnvAp17ICuc4+LiJJ9UOY6DxWLRdZZwqFK/fn1cuHABTqfzSsdJr5uIEIBeixJ6o2c4g1KaNWsmudxyWTgrtVlP4Sz0brPx2gykpqYiGCnPcRw5ncIEh8OBHj168J+nT5+O6dOnS6578uRJ7Nq1C7169fJrG2INy+4FNTSs7F1vpmT0oUrfvn2xdOlSd+EMet1EmB8XeYUInYmUKG1tNHa7XXI5E6e+QjB69uyJbdu26RqqIcYswrlhw4b4C8D+AwfQXKGnXow59oQIFpvNhu3bt/tcr7i4GKNGjcIbb7zh9xwILTWs4kf87OxsvgISADRu3FgTg8IJJpYdDgeioqIAUIwzERqQx5nQG9ZfmkXoAXAb84RYL9voy+PcsmVL7N692zBvupnuY/bwQG+rCSXY7XaMGjUKEydOxMiRI4NuT00N6/Mx+LvvvkOrVq3QrFkz9OvXD02bNsWQIUMC3mB1gnWurAIVj4kGBoKQ4uzZs0abQFQzzOhxlvMUKw3VsNlssNvtuoZqEESow3Ecpk6dinbt2uEf//hHUG1poWF9Cuf//Oc/+PPPP9G6dWucOHEC69atQ+/evYPaaHUh4nKnaqanfoJQAoVqEXpjxhhnuZAlJqh9CWL2ptGoybY09hChyKZNm/DFF1/gl19+QZcuXdClSxesXr06oLa00LA+hXNkZCTq1q0Ll8sFl8uFAQMGKIpNIapeOcbHx3t0XuRvJszKQw89BACYPHmywZYQ1Q0WopGbm2uwJVdEvJwtzFZfwpl9v3btWhWt8w8zhb4EAz0EVB+uueYacByHvXv3Yvfu3di9ezeGDh0aUFtaaFifj/gJCQkoLi7Gtddei4kTJ6JevXqIlaikREhTWFiIc+fOIb527aoFdPMTJiYhIQGAuYpRENULM3qeA+X333832oTwIkweAgj9YBr2uuuuU03D+vQ4DxgwAJcuXcKbb76JjIwMtGjRAt9//31QG61unDh50mgTCEIRnTt3xu23304xmYRhOMVzQgxALS/twYMHVWknGMLF40wQgbBixQrExMTg9ddfV03D+hTODocDgwcPRv/+/VFUVIRx48ahbt26QW2UIAhzUqtWLUycONFoM4hqTCi9kt+yZYvX743KPvXcc88BACorKw3Zvi+KAsiswXEchTkSfhMbG4uIiAiUlpbipptuwqRJk4J+mPQpnJ966ins378f77zzDs6dO4d+/frhhhtuCGqj1Q2hByV0hgSCIAj9Cacc4vfccw8A4NFHH9V1u+np6QCAv//+W9ft+qJdu3YAzPFWgagefPDBB0hJSUGnTp3Qo0cPdO/e3a34SiAoDiarV68eUlJSULduXWRnZwe10epGQUGB+wJ6dUYQBOGBxWJBamqq0WYgMTER2dnZaNO6dVDtsHjtmjVrqmGWYlio1d69e9GtWzddt+2N6Bo1AABnz51DQmKi/w3Q2En4yauvvop9+/YhKSlJtTZ9Cud3330XixcvRk5ODsaMGYMPP/wwoHrhBEEQBOGNH374wWgTAAADr78eLpeLTykqR2sfwlpp9g21MeschajLwnnXrl0B6QiSzYS/tGjRQvUHV5/C+cyZM3jjjTfQpUsXVTdcnaGbnyAIwrxYIyJgVSA+W7Vq5fX7vLy8qvZ0Lrkt3J6ZJgfGxcUZbQJRzZg9ezb69OmDXr16ocblBzcAeOuttwJu06dwnj17dsCNE1fIu3gRderWpXR0BEEQYUJZWZnX71l5ab2FczgSSpNGCfNwzz334Prrr0d6erpq92H4JMw0OX9s3ozhw4dXfTCRB4AgCIIIjF9++QX//Oc/Zb9nEx2NDJ0wk8c5aMJpXwhdsNvteO2111Rtkx6DNYZ1mJcuXTLYEoIgCEJPUlJSAJDHmSCMYsiQIZg3bx7OnTuHvLw8/l8wkMdZY6Se9umZmSAIIvxhGS2MFM7h5HEOnz0h9GLhwoUA3MOOLRYLjh8/HnCbJJw1RtxhUpQWQRBEeDB16lSv37P+n/IWE4QxnDhxQvU2SThrzLXXXot169YBAJwOh8HWEARBEGrQq1cvxN1yi9d1mHCuqKjQwaJqQBh5zwl9sNvteO+997BhwwYAQP/+/XHPPfcgMjIy4DYp8EpjWIwbAJSUllJWDYIgiDAgLi7O5+DLhLMRoRrR0dG6b1MJgwcPBlAlaPyFZDPhL/fddx927NiB+++/H/fffz927NiB++67L6g2yeOsI3v27KnqaOmpmSAIotpgRJzxfffdh9dff910Mc5M0DscDr+8fpSOjgiEbdu2Yc+ePfzn66+/Hp07dw6qTfI468jp06eNNoEgCILQGSNEH6uWZlbByV1O1UcQWhIREYFjx47xn48fPx50ekjyOOtAQkICCgoKAACVlZXGGkMQBEHoihHilXmazTYxkXmcz1+4gObNm/v3Y5N5zwnz88orr2DAgAFo3rw5OI7DqVOn8OmnnwbVJglnHejevTs/QZDjOIrTIgiCqEYYIZxZXPXhw4d137Y3WHjG5s2b/RLOZvWcE+Zm4MCBOHr0KH8ftGnTxq30diCQcNYB4QRBuvkJgiCqF0YK5/Pnz+u+bYIwEzt27MDJkyfhcDiwe/duAMAdd9wRcHsknHWmvLycXjcRBEFUE5588km+EIqepKWlASBnDVG9uf3223Hs2DF06dKFj222WCwknEOJixcvolWrVkabQRAEQejAtddea8h22ZvOkydPGrJ9LSCXE+Ev27dvx4EDB1TNLkNZNQiCIAgizLDZwtAvRm9rCT/p2LGj6uFKYXhnmZORI0di6dKlRptBEARBECEHhZwQgZCbm4v27dvjqquucpsU+N133wXcJglnnYiJieH/pmdmgiAIgiAIbXn66adVb5OEs440aNAA+fn5RptBEARBEIZTXl7uV2lwcjoR/tKvXz+3zxs3bsTChQs9lvsDCWcdsVgsVa+bKE6LIAiCqKbUrFkTpaWlgB/hFxSqQQTKrl278NVXX+Gbb75Bs2bNMGrUqKDaI+FMEARBEGFKs2bNjDbBg169euHXX3/1v6ohOZ0IhRw5cgQLFy7EwoULkZSUhHHjxoHjOPz6669Bt01ZNXSEeZzp1icIgiC05uqrr8agQYOMNsODpKQkAMDyFSsMtoQIV9q2bYtffvkFK1euxMaNG/HQQw/xeZyDhTzOOkOvmwiCIAg9eOqpp4w2QZJAx0FyOhFKWbp0KRYtWoQBAwYgIyMD48ePV01/kcdZRywWS9WrKXrdRBAEQVRTbIF6/mjsJBRyyy23YNGiRTh06BAGDBiAN954A9nZ2bjvvvvw008/BdU2CWedcblcyMrKMtoMgiAIgjCEiHAszkKYktjYWNx22234/vvvkZmZia5du+Kll14Kqk0SzgZw6dIlo00gCIIgCIKoNiQmJmL69OlYt25dUO2QcNYRVivd75nEBEEQBFGNoflBhFkg4WwAJJwJgiAIwj8owpkwAyScdYR5nHt0726wJQRBEAQRYtDkQMIEkHA2gNjYWKNNIAiCIIiQgUI1CLNgmHB2Op3o2rUrhg8fDgA4ceIEevXqhZYtW2LcuHGorKw0yjTNYB5nemomCIIgqjNRUVEA/BPENHISZsAw4fzmm2+iXbt2/Od//etfeOSRR/D3338jMTERH3/8sVGmEQRBEAShIUw4Hz1yxGBLCMI/DBHOmZmZWLVqFaZNmwag6onzl19+wejRowEAkydPxvLly40wTVMs5GkmCIIgCLRv3x4AUFBQYKwhBOEnhgjnmTNn4uWXX4bVWrX5ixcvIiEhAbbLSdHT0tLCskgICWeCIAiCAFq2bAkAOPr33wZbQhD+oXv5npUrV6JevXro3r07fvvtN79/P2/ePMybNw8A4HA4kJOTo7KFweGorISlrEzyu/KICLhiYlBgt8Mlsw4AcJWVsJlov/Lz8402gdAIOrfhCZ1X33jrq5VgRD8d6udVfMxdMTEAgFwF56HCZkOBwwGLycZHtQj1c6sma9aswcMPPwyn04lp06Zh1qxZRpvkhu7CedOmTfjuu++wevVqlJeXo7CwEA8//DAKCgrgcDhgs9mQmZmJ1NRUyd9Pnz4d06dPBwDUrFkTycnJeprvE3tUFCyXOwMx0U4nrGVlSIyMRKLMOkBVhxxpsv0y23Em1IPObXhC59U73vpqJRjVT4fyeRUfc+tlwZyk4DxE2e1IiIxEUlSU6cZHtQjlc6sWTqcTDzzwAH7++WekpaWhZ8+eGDFiBB/aYwYsnIE5Xn777Te8+uqrWLlyJcaMGYNRo0Zh/PjxuPfee9GpUyfcf//9Xn9fs2ZNHDt2TBdba/zyC2q9/rrP9biCAiAi4srvjhwBZ7GgslUrFBUVoby8HImJiXxYiiROJywJCcEbrRJ2hwOR3uwlQhY6t+EJnVffiPtqITUuT1iraN1a5sccahw9CldiIhzNm8tuw3bkCKxFRahUKXe/0vNqLSiA7dgx2Nu1A1ezpirbVgPrsWOwFRSgokULICKCf2MsFIxyx76goACxsbGItFpNNT6qhZH3bOF//gP7VVfptr2WLVuipKRE8rvNmzfj6aefxo8//ggAmD17NgDg//7v/3Szzxem6VlfeukljB8/Hv/+97/RtWtXTJ061WiT3OAiIsApyL/sKiuDhV38LhcAwMJx4KKj4Sgvh93hgKtGDXCRkfLbcjhgNVGuZ1dlJbjLM6CJ8ILObXhC59U3bn21DFx0tORy6+UJbdb8fK/jgrWo6EpbKvTpSs+rbceOqv+PHkVlnz5Bb1ctbJePW0RhIRwNGsB++fhLHWfxMrvNBleNGnBZraYaH9XC0HtWZ8HucDjQo0cP/rMwkiArKwuNGjXiv0tLS8OWLVt0tc8Xhgrn/v37o3///gCA5s2bY+vWrUaa45XKfv2Q16+fz/Xsq1bBUrs2AMBSWYm0SZMAADn//jf+3LwZx44fx9ChQ5GYmCjbBnfpEiKHDVPHcBXIycmhV0hhCp3b8ITOq2+EfbWYRmPHAqjqt6WIPH4cKbNmwd6xI/IWLZLdRnKvXrCdOYOCd9+FUyAGAkXpeY17+mnUmjcPRU8+iZJ77gl6u2qRMHAgYg4eRN4996CiUyd8/eWXAICJEyfy68gd+x9//BHdunWrCtUw0fioFtXpnrXZbNi+fbvRZgQMVQ7UE8qqQRAEQRABQSNo+JOamoozZ87wn73NeTMKEs46Qjc9QRAEQbhD5bQJRs+ePXH06FGcOHEClZWVWLRoEUaMGGG0WW6QcNYT8jgTBEEQWhMiQrRp06YAKBUbcQWbzYb//e9/uPHGG9GuXTuMHTsWHTp0MNosN0wzObA6YBH9TxAEQRDVBfHYx7JLUXEwQsjQoUMxdOhQo82QhTzOekKdA0EQRPXBaM+vycecOnXqAAAu5ub6XJfjONPvD1E9IOFsBHTzEwRBhD5K+3Lq8yVpdjlUY4vCjFp0FAkzQMJZR+imJwiCIIgqrDIFaAjCzJBw1pPLXgcS0ARBEITmGB0q4gOrVV6CfPnll8jKynJfSJ57wgSQcNYQcZdFtzxBEEQYYXJhajr8PF579uzRyBCCCBwSznpCT8sEQRDVD6MEdoiPOcI0dRzHkfOJMAUknHWET7kT4p0ZQRAEoQDySLtDYx8RBpBwJgiCIIhAoKwaBFHtIOGsI9R1EgRBVCMMEsyWMPJ02+12AJTHmTAPJJx1hKojEQRBENUWCUHfskULAIDL5ZL8yeLFizU1iSD8hYQzQRAEQYQhXAg4a5hDiZMRzgRhNkg4G4D5uzKCIAhCljAKhTAEgaCPqVkTwOVQDF8/08wgglAOCWcdoVANgiCI8MGnR9dggR0Ksc5RUVEAAKcXj7PT6dTLHILwCQlnLRF3qpSOjiAIotphfvlqHK1atQIAnD51CmWlpZLrFBcV0eRAwjSQcNYRuuUJgiAI4gqs7PbWbdtw4OBBfnmPHj34v1euWqW7XQQhBwlnPbn8tEwCmiAIIvQxeyiE6SYH+jhehw4d4v9u06aN23dlZWWamEQQ/kLCWUdM1oURBEEQOkB9f/BUVFTA4XAYbQZBkHDWFbM9/RMEQRCESWnXrp3b54qKCoMsIYgrkHDWEZLNBEEQ4YOvUAjDQjnMGkLip/Ooa9eubp9ZPDRBGAldhXpCHmeCIIhqh0llrOkRp3Ctl5xskCUEcQUSzgRBEAQRjpjNWWNWTzhB+AEJZx2hAigEQRDVB8OzWphVqIqOS3R0tEGGEIT/kHDWEqM7TYIgCEJ1zJ6GLtRgqedq167t8V1GRgb/d4TNpptNBCEHCWcd4WU0CWqCIAiCAABEXJ70d+nSJY/v6tatCwBo2aIFvbUlTAE9vukI3fQEQRBhhFmzavAGhMaYk9KgAbBrl+z3EydO1NEagvAOeZz1hCoHEgRBEIQbiYmJRptAEIoh4UwQBEEQgaDUoxwinl+CIHxDwllH+FAN6kQJgiAIgiBCDhLOOkJymSAIohqid6yz0bHVBBHGkHAmCIIgCIIgCAWQcNYTmhxIEAQRPvgKuyPPL0GEHSScdYQEM0EQBEEQROhCwllPaFIgQRBE9UPvvp/GGoLQDBLOOkJdGUEQBKE5IRgi0qRJE6NNIAhFUOVAPSEvAEEQRPWB+nzFNG7cGCUlJUabQRA+IY+zjvBdKHWmBEEQoQ/15arRuHFj3HjjjUabQRA+IeGsJ9TJEgRBVB9CMGRCU+h4EGEACWcdsYj+JwiCIEIYEoKBQU4kIoQh4awn1FkQBEFUP/Tu+0nQE4RmkHA2AhLQBEEQ1QcSsu7Q8SAC5PHHH0fbtm3RqVMn3HrrrSgoKNDdBhLOOmIhwUwQBEFUV2gMJIJk0KBB2LdvH/bu3YvWrVtj9uzZuttAwllLRJ0EdRkEQRBhhFmFoFntIk8zESSDBw+GzVaVSbl3797IzMzU3QYSznpyuTMzaZdGEARBENpjVmFPhBSffPIJhgwZovt2qQCKjlCoBkEQBKE55NklTIzD4UCPHj34z9OnT8f06dP5zzfccAPOnz/v8bsXXngBN998M/+3zWbDxIkTtTdYBAlngiAIgtASo5wm5KwhTIjNZsP27dtlv1+7dq3X33/22WdYuXIl1q1bZ4hDkoSzjpDHmSAIgiAIIjDWrFmDl19+GevXr0fNmjUNsYFinHWEZDNBEEQYQKEQBGEIDz74IIqKijBo0CB06dIF9957r+42kMfZCMjzTBAEEfqYtS8nYU+EKX///bfRJpDHWU8oVIMgCCKMIIEaGDQWEiGM7sL5zJkzGDBgANq3b48OHTrgzTffBADk5eVh0KBBaNWqFQYNGoT8/Hy9TdMcEs4EQRBhAPXlBFFt0V0422w2zJ07FwcOHMCff/6Jd955BwcOHMCcOXMwcOBAHD16FAMHDsScOXP0Nk19qHMlCIIg9B4LzD72kKeeCGF0F84NGjRAt27dAABxcXFo164dsrKysGLFCkyePBkAMHnyZCxfvlxv0zTHQgVQCIIgQh9/hR8JRYIIGwyNcT558iR27dqFXr164cKFC2jQoAEAICUlBRcuXDDSNE2gUA2CIAhCc0ioE4RmGJZVo7i4GKNGjcIbb7yB+Ph4t+8sFousyJw3bx7mzZsHoKr6TE5Ojua2+oOjshKWsrKqDy4XGgHgLBbklpXhktMJV0wM8ioqEOWlDa6yEjYT7Vc4xpsTVdC5DU/ovPrGra8W0ejy/7ky39esqEB9+B6D6jqdiEDVHB57ZGRwBkP5eY0sK0MsgOKSElw00VhSy+VCNIBLlZUoDvDYm218VAu6Z0MHQ4Sz3W7HqFGjMHHiRIwcORIAUL9+fZw7dw4NGjTAuXPnUK9ePcnfCksz1qxZE8nJybrZrQR7VBQsMTFVH1wufnlSTAwqbDZYy8pQJzoa0dHRsm1wlZWINNl+me04E+pB5zY8ofPqHbe+WoYkme+jatQAANgiI70e54iICABAnTp14FLpfCg5rzGX7a5VqxasJroOIq1VL7lr16iB6ACPvRnHR7WgezY00D1Ug+M4TJ06Fe3atcM//vEPfvmIESMwf/58AMD8+fP5euThBIVqEARBVCMoZIIgwg7dPc6bNm3CF198gfT0dHTp0gUA8OKLL2LWrFkYO3YsPv74YzRp0gSLFy/W2zSCIAiCUB9ymhBE2KC7cL7mmmvAyTyFr1u3Tmdr9IU8zgRBEGGA2T3JZrXPrHYRhB9Q5UAdIeFMEAQRRlCfThDVDhLOBkBdLUEQRBhgVg8qCXqC0AwSzjpCHmeCIIgwQGlfTn0+QYQdJJx1hO9CqTMlCIIIf8zqkSYIImBIOBMEQRBEOEGCnSA0g4SzjrBQDfI3EwRBhDChIkzp7SZBqA4JZz2hTowgCCJ8oD6dIKodJJx1hLpYgiAIgiCI0IWEs54w7wR5KQiCIAiCIEIO3SsHVissFnARESi4446qjwabQxAEQeiIQbHQ9g4dAACOZs0M2b4soRIbThBeIOGsJRYLMhcuFHwk6UwQBGF2nHFxcKSkqNegzn1/2cSJsHftCsdlAW02OBoLiRCGhDNBEARBCDj78cdGmxAcFotpRTNBhDoU46wnlI6OIAiCIAgiZCHhrCMkmAmCIAiCIEIXEs56QnFdBEEQBEEQIQsJZyMgAU0QBEFUMwqHDwdntcLeuLHRphBEwNDkQB2hrBoEQRBEdaW8QwdkLlpktBkEERTkcdYRi+h/giAIgiAIInQg4awn5HEmCIIIH6hPJ4hqBwlnHaEuliAIgiAIInQh4awn5J0gCIIgCIIIWUg46wjJZoIgiGoExxltAUEQKkPCmSAIgiD8wVo1dHIxMcrWp7eNBBE2kHDWE+o8CYIgQp7KFi1QcMstKPjf/4w2hSAInSHhrCO8bCYBTRAEEbpYLCgcNgyuevWMtoQgCJ0h4awjVACFIAiCIAgidCHhTBAEQRAEQRAKIOGsI8zjTH5ngiCI8KfymmsA+DGJkCAI00PCWU8oVIMgCKLaUDB3LrJ//x1cfLzRphAEoRIknHWEJgcSBEFUI2rUgLNFC6OtIAhCRUg46wkJZoIgCIIgiKCYO3cuLBYLcnNzdd82CWeCIAiCIAgiJDhz5gx++uknNG7c2JDtk3DWEYvof4IgCIIgCEI5jzzyCF5++WXDUvzaDNlqdYVCNQiCIAiCqMY4HA706NGD/zx9+nRMnz5d0W9XrFiB1NRUdO7cWSvzfELCWUdINhMEQRAEUZ2x2WzYvn277Pc33HADzp8/77H8hRdewIsvvoiffvpJS/N8QsJZT8jjTBAEQRAEIcvatWsll//11184ceIE723OzMxEt27dsHXrVqSkpOhmHwlnHeHjcUhAEwRBEARBKCY9PR3Z2dn856ZNm2L79u1ISkrS1Q6aHEgQBEEQBEEQCiCPs46Qn5kgCIIgCCJ4Tp48ach2yeOsI0alTiEIgiAIgiCCh4QzQRAEQRAEQSiAhLMBkOeZIAiCIAgi9CDhrCMkmAmCIAiCIEIXEs56QsKZIAiCIAgiZCHhrCMkmwmCIAiCIEIXEs56Qh5ngiAIgiCIkIWEM0EQBEEQBEEogISzjtDkQIIgCIIgiNCFhLMBkIAmCIIgCIIIPUg46wgJZoIgCIIgiNCFhLPO1KxZ02gTCIIgCIIgiAAg4awzt956q9EmEARBEARBEAFgM9oAgiAIgiAIAHDGxqLs6quNNoMgZDGVx3nNmjVo06YNWrZsiTlz5hhtDkEQBEEQOnL200+RP3260WYQhCymEc5OpxMPPPAAfvjhBxw4cAALFy7EgQMHjDaLIAiCIAiCIACYSDhv3boVLVu2RPPmzREVFYXx48djxYoVRptFEARBEARBEABMJJyzsrLQqFEj/nNaWhqysrIMtIggCIIgCIIgrhBykwPnzZuHefPmAQAcDgdycnIMtsgdR2UlLGVlQbXBVVbCZqL9ys/PN9oEQiPo3IYndF59E2xfbUQ/HernNRzHR7UI9XNbnTCNcE5NTcWZM2f4z5mZmUhNTfVYb/r06Zh+eeJAzZo1kZycrJuNSrBHRcESExNUG1xlJSJNtl9mO86EetC5DU/ovHon2L7aqH46lM9ruI6PahHK57Y6YZpQjZ49e+Lo0aM4ceIEKisrsWjRIowYMcJoswiCIAiCIAgCgIk8zjabDf/73/9w4403wul04q677kKHDh2MNosgCIIgCIIgAJhIOAPA0KFDMXToUKPNIAiCIAiCIAgPTBOqQRAEQRAEQRBmhoQzQRAEQRAEQSiAhDNBEARBEARBKICEM0EQBEEQBEEogIQzQRAEQRAEQSjAwnEcZ7QRgWK1WhETZDJ1wjcOhwM2m6kSsBAqQec2PKHzGp7QeQ1fqtO5LSsrg8vlMtqMgAlp4UzoQ48ePbB9+3ajzSA0gM5teELnNTyh8xq+0LkNHShUgyAIgiAIgiAUQMKZIAiCIAiCIBRAwpnwyfTp0402gdAIOrfhCZ3X8ITOa/hC5zZ0oBhngiAIgiAIglAAeZwJgiAIgiAIQgEknEOQM2fOYMCAAWjfvj06dOiAN998EwCQl5eHQYMGoVWrVhg0aBDy8/MBAIcOHcLVV1+NGjVq4NVXX+XbKS8vx1VXXYXOnTujQ4cOeOqpp2S3mZGRgYSEBAwfPtxt+cSJE9GmTRt07NgRd911F+x2u+Tv5db78ssv0alTJ6Snp6NPnz7Ys2dPUMcmlFHrvDKcTie6du3qcc6EzJ8/H61atUKrVq0wf/58fvmTTz6JRo0aoVatWl5t3rFjB9LT09GyZUvMmDED7AXW008/jdTUVHTp0gVdunTB6tWr/T4e4UQonlu59U6dOoWBAweiU6dO6N+/PzIzMxUfh3DDLOe1tLQUw4YNQ9u2bdGhQwfMmjVL9vdy9+zjjz+Otm3bolOnTrj11ltRUFAQ6GEJC0Lx3Hq7txcvXszvy2233ebXsSBEcETIcfbsWW7Hjh0cx3FcYWEh16pVK27//v3c448/zs2ePZvjOI6bPXs2989//pPjOI67cOECt3XrVu6JJ57gXnnlFb4dl8vFFRUVcRzHcZWVldxVV13Fbd68WXKba9eu5b777jtu2LBhbstXrVrFuVwuzuVycePHj+feffddyd/Lrbdp0yYuLy+P4ziOW716NXfVVVcFelhCHrXOK2Pu3LnchAkTPM4Z4+LFi1yzZs24ixcvcnl5eVyzZs34c7F582bu7NmzXGxsrFebe/bsyW3evJlzuVxcRkYGt3r1ao7jOO6pp56StKm6EornVm690aNHc5999hnHcRy3bt06btKkSX4cifDCLOe1pKSE++WXXziO47iKigrummuu4e9FMXL37I8//sjZ7XaO4zjun//8J29zdSUUz63cPXvkyBGuS5cufB9w4cKFAI4IwSCPcwjSoEEDdOvWDQAQFxeHdu3aISsrCytWrMDkyZMBAJMnT8by5csBAPXq1UPPnj0RGRnp1o7FYuGfTO12O+x2OywWi+Q2Bw4ciLi4OI/lQ4cOhcVigcViwVVXXSXrfZJbr0+fPkhMTAQA9O7du1p7r9Q6rwCQmZmJVatWYdq0abLb+/HHHzFo0CDUqVMHiYmJGDRoENasWQOg6lw0aNDAq73nzp1DYWEhevfuDYvFgjvuuIO3jXAn1M6tt/UOHDiA66+/HgAwYMAArFixwmdb4YpZzmvNmjUxYMAAAEBUVBS6desm2Zd6u2cHDx7MF+Co7n0xEHrnFpC/Zz/88EM88MAD/Fhbr1495QeC8ICEc4hz8uRJ7Nq1C7169cKFCxf4myYlJQUXLlzw+Xun04kuXbqgXr16GDRoEHr16hWQHXa7HV988QUyMjICXu/jjz/GkCFDAtp+uBHseZ05cyZefvllWK3yt3hWVhYaNWrEf05LS0NWVpZiG7OyspCWlib7+//973/o1KkT7rrrLv51JhEa59YbnTt3xtKlSwEAy5YtQ1FRES5evKhK26GMWc5rQUEBvv/+ewwcOFDy997uWcYnn3xCfbGAUDi33jhy5AiOHDmCvn37onfv3vxDNBEYJJxDmOLiYowaNQpvvPEG4uPj3b5j3l1fREREYPfu3cjMzMTWrVuxb9++gGy5//77cd111+Haa68NaL1ff/0VH3/8MV566aWAth9OBHteV65ciXr16qF79+5amumV++67D8eOHcPu3bvRoEEDPProo4bZYibC4dy++uqrWL9+Pbp27Yr169cjNTUVERERhtljBsxyXh0OByZMmIAZM2agefPmAbXxwgsvwGazYeLEiUHZEi6Ew7l1OBw4evQofvvtNyxcuBB33313tY9hDwYSziGK3W7HqFGjMHHiRIwcORIAUL9+fZw7dw5A1Ss5f17HJCQkYMCAAVizZg22bNnCT+r67rvvfP72mWeeQU5ODl577TV+2Y033oguXbq4vZqSWg8A9u7di2nTpmHFihWoW7euYpvDETXO66ZNm/Ddd9+hadOmGD9+PH755RdMmjTJ47ympqbizJkz/O8yMzORmpoq2y57O9GlSxf897//RWpqqtsrQ+Hv69evj4iICFitVtx9993YunVrwMckXAilc+uNhg0bYunSpdi1axdeeOEFAFX9R3XFTOd1+vTpaNWqFWbOnAnAv3sWAD777DOsXLkSX375pSLHS7gTSufWG2lpaRgxYgQiIyPRrFkztG7dGkePHg3kkBAATQ4MRVwuF3f77bdzDz/8sNvyxx57zG3SwuOPP+72vXjCVnZ2Npefn89xHMeVlpZy11xzDff999/LbvfXX3/1mNjw4YcfcldffTVXWlrq1Wa59U6dOsW1aNGC27Rpk9ffVwfUOq9CpM4Z4+LFi1zTpk25vLw8Li8vj2vatCl38eJFt3X8nRy4atUqjuOqJtYwXnvtNW7cuHFe2wl3QvHcyq2Xk5PDOZ1OjuM47oknnuD+85//KGonHDHTeX3yySe5kSNH8udGDrl79ocffuDatWvHZWdn+9zv6kAonluG+J794YcfuDvuuIPjuKr7Ny0tjcvNzVXUFuEJCecQ5Pfff+cAcOnp6Vznzp25zp07c6tWreJyc3O566+/nmvZsiU3cOBA/qY7d+4cl5r6/+3dPUsjXRjG8Sv6xBeIaGGhjCBkFJXJ4EBaRSzECPoNAoIpBMVC8KWwUD+HaGthsBAEK7HSQlKIWlgIgqVY2AkxuZ9iYdiFzTLLujuG/H9dhjnJxTlMuBiGOY51dHRYZ2enOY5jb29vdnNzY0EQmO/75nme7e7u1vzNsbEx6+7utra2NnMcx87OzszMrLm52dLpdJij1nfUOq9QKFhXV1d4PJvNfvJs1Y/PWtfv/eqP2sxsf3/fXNc113Xt4OAgPL6+vm6O41gikTDHcWx7e/un46+vr83zPEun07a8vGzVatXMzPL5vGUyGfN93+bm5n4o0o2oHte21nlHR0c2MDBgg4ODVigU7P39/c8mp459lXV9fn42STY8PBzm2Nvb++n4Wtes67rW19cXjl9cXPyMKapb9bi2ta7ZarVqq6urNjIyYplMxg4PDz9hhhoXOwcCAAAAEfCMMwAAABABxRkAAACIgOIMAAAAREBxBgAAACKgOAMAAAARUJwB4C97fX0NNyvo6emR4zgKgkCpVEpLS0txxwMARMTr6ADgH9rZ2VEqldLa2lrcUQAAv4k7zgAQk4uLC83Ozkr6Vqjn5+c1Pj6u/v5+HR8fa2NjQ77vK5fLqVwuS5JKpZImJiaUzWY1PT0dbv8LAPj7KM4A8EU8Pj7q/PxcJycnyufzmpyc1O3trdrb23V6eqpyuayVlRUVi0WVSiUtLCxoa2sr7tgA0DD+izsAAOCbmZkZJZNJ+b6vSqWiXC4nSfJ9X09PT3p4eNDd3Z2mpqYkSZVKRb29vXFGBoCGQnEGgC+itbVVktTU1KRkMqlEIhF+/vj4kJnJ8zxdXV3FGRMAGhaPagBAnRgaGtLLy0tYnMvlsu7v72NOBQCNg+IMAHWipaVFxWJRm5ubGh0dVRAEury8jDsWADQMXkcHAAAARMAdZwAAACACijMAAAAQAcUZAAAAiIDiDAAAAERAcQYAAAAioDgDAAAAEVCcAQAAgAgozgAAAEAE/wM5vem42hrfxAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from merlion.post_process.threshold import AggregateAlarms\n",
    "\n",
    "# We use a custom post-rule (AggegateAlarms instead of the default Threshold),\n",
    "# where we suppress all alarms for a day after the most recent one is fired.\n",
    "threshold = AggregateAlarms(alm_threshold=3.0, alm_suppress_minutes=24*60)\n",
    "model2 = StatThreshold(StatThresholdConfig(threshold=threshold))\n",
    "\n",
    "# Train the model as before\n",
    "model2.train(train_data, train_labels)\n",
    "\n",
    "# Visualize the model's anomaly scores with the new post-rule\n",
    "fig, ax = model2.plot_anomaly(test_data, filter_scores=True)\n",
    "plot_anoms(ax, test_labels)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quantitative Evaluation\n",
    "\n",
    "Finally, you may quantitatively evaluate the performance of your model as well. Here, we compute precision, recall, and F1 score for `model2` above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model Evaluation\n",
      "Precision: 0.5000\n",
      "Recall:    1.0000\n",
      "F1 Score:  0.6667\n"
     ]
    }
   ],
   "source": [
    "anom_labels2 = model2.get_anomaly_label(test_data)\n",
    "\n",
    "print(\"Model Evaluation\")\n",
    "print(f\"Precision: {TSADMetric.Precision.value(ground_truth=test_labels, predict=anom_labels2):.4f}\")\n",
    "print(f\"Recall:    {TSADMetric.Recall.value(ground_truth=test_labels, predict=anom_labels2):.4f}\")\n",
    "print(f\"F1 Score:  {TSADMetric.F1.value(ground_truth=test_labels, predict=anom_labels2):.4f}\")"
   ]
  }
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